Creator · TheSmokeDev
Last updated · Sep 6, 2026
Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or gen
Creator · TheSmokeDev
Last updated · Sep 6, 2026
Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or gen
Creator · TheSmokeDev
Last updated · Sep 6, 2026
Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or gen
Creator · TheSmokeDev
Last updated · Sep 6, 2026
Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or gen
Sandbox only
Install targets
Codex install prompt
Install the "geo-llmstxt" agent skill from https://github.com/TheSmokeDev/geo-skills/tree/main/skills/geo-llmstxt. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or generate new ones from scratch by crawling the site. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"thesmokedev-geo-llmstxt","task":"Install geo-llmstxt","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Maintenance
fresh
3d since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
22
60/100 Quality · 71/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Low GitHub adoption signal
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
22 GitHub stars
Repo activity
22 stars, 6 forks
Maintenance
3d since push
License
MIT
Install
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxtDo not use when
Alternative
46.6K Stars
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Alternative
46.6K Stars
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Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/thesmokedev-geo-llmstxt/install
Agent should check
Copy prompt
Task: Use geo-llmstxt in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/thesmokedev-geo-llmstxt/install
Install command: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/thesmokedev-geo-llmstxt/install
LLM text format
/api/skills/thesmokedev-geo-llmstxt/install?format=text
Find alternatives
/api/skills/search?q=geo-llmstxt&limit=3
Agent prompt
Use geo-llmstxt for this task. Review https://www.openagentskill.com/api/skills/thesmokedev-geo-llmstxt/install, then install with: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxtRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/thesmokedev-geo-llmstxt
LLM text
/api/registry/manifest/thesmokedev-geo-llmstxt?format=text
Install alias
/api/registry/install/thesmokedev-geo-llmstxt
Recommend
/api/registry/recommend?task=Use%20geo-llmstxt%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
FIX22 GitHub stars
Stars/forks activity
FIX22 stars, 6 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Manage pipeline work
I need my agent to enrich leads, update CRM records, and prepare sales follow-ups.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Similar skills that may fit this task.
When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," "CTA copy," "value proposition," "tagline," "subheadline," "hero section copy," "above the fold," "this copy is weak," "make this more compelling," or "help me describe my product." Use this whenever someone is working on website text that needs to persuade or convert. For email copy, see emails. For popup copy, see popups. For editing existing copy, see copy-editing. For the offer underneath the copy (bonuses, guarantees, value framing), see offers.
When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.
Determine the next version, update the marketing site, and run the full release pipeline.
dontbesilent 商业工具箱主入口。双模式:任务前路由(你的问题该用哪个 skill)+ 任务后导航(刚做完诊断,下一步该干什么)。 触发方式:/dbs、/商业、「帮我看看」、「下一步怎么走」 Main entry point for dontbesilent business toolkit. Dual mode: pre-task routing + post-task navigation. Trigger: /dbs, "help me with my business", "what's next"
--- name: geo-llmstxt description: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or generate new ones from scratch by crawling the site. allowed-tools: - Read - Grep - Glob - Bash - WebFetch - Write ---
# llms.txt Standard Analysis and Generation Skill
## Purpose
This skill handles everything related to the `llms.txt` convention (proposed by Jeremy Howard in September 2024) -- a single Markdown file at the domain root that states your canonical business facts and points at your most important pages.
**Positioning as of August 2026: llms.txt is a 30-minute anti-hallucination facts hedge, NOT an AI-visibility lever.** Do not sell it to clients as a ranking or citation play -- the evidence says it does not move citations:
- **Google Search Central, 2026 (official):** "You don't need to create new machine readable files... to appear in generative AI search." Google has stated plainly that no AI-specific file is required or rewarded. - **Zyppy meta-analysis of 54 studies (via digitalapplied.com, Jun 2026):** llms.txt scores **2.0 out of 10 -- the lowest of all 23 measured GEO factors**. - **SE Ranking (seranking.com/blog/llms-txt, Nov 2025):** found **zero correlation** between having an llms.txt file and AI citation/visibility.
## What llms.txt Is Actually For
What remains is real but modest. A well-crafted llms.txt is worth roughly 30 minutes of effort because it:
1. **Reduces misrepresentation:** Key facts (pricing, features, locations, founding date) are stated explicitly in one place, reducing AI hallucination about your business when a system does consult the file. 2. **Controls the narrative:** You choose which pages and facts are presented as canonical, rather than leaving inference to a crawler. 3. **Costs almost nothing:** It is a single static Markdown file. There is no maintenance burden beyond updating it when facts change.
What it does **not** do: improve rankings, increase citation rates, or substitute for indexation, crawlability, or content quality. Treat it as hygiene -- like a favicon or a humans.txt with a purpose -- and never present it in an audit as a visibility win.
---
## The llms.txt Specification
### File Location
The file MUST be located at the root of the domain: ``` https://example.com/llms.txt ```
### Format Specification
The file uses Markdown formatting with specific conventions:
```markdown # [Site Name]
> [One-sentence description of what the site/business does. Keep under 200 characters.]
## Docs
- [Page Title](https://example.com/page-url): Concise description of what this page covers and why it matters. - [Another Page](https://example.com/another-page): Description of content.
## Optional
- [Less Critical Page](https://example.com/optional-page): Description. ```
### Detailed Format Rules
**1. Title (Required)** ```markdown # Site Name ``` - Must be the first line of the file. - Should be the official business/site name. - Use the H1 heading format (single `#`).
**2. Description (Required)** ```markdown > Brief description of the site/business ``` - Must appear immediately after the title. - Use Markdown blockquote format (`>`). - Keep under 200 characters. - Should clearly state what the business does and who it serves. - Avoid marketing fluff -- be factual and specific.
**3. Main Sections (Required -- at least one)**
Use H2 headings (`##`) to organize pages by category. Common section names:
| Section Name | Purpose | Example Content | |---|---|---| | `## Docs` | Primary documentation or key pages | Product pages, service descriptions, core content | | `## Optional` | Secondary pages worth knowing about | Blog posts, supplementary resources | | `## API` | API documentation | API reference, authentication guides | | `## Blog` | Blog or news content | Recent/popular articles | | `## Products` | Product catalog | Product pages, pricing | | `## Services` | Service offerings | Service descriptions, process pages | | `## About` | Company information | About page, team, mission | | `## Resources` | Educational/reference content | Guides, tutorials, whitepapers | | `## Legal` | Legal documents | Terms of service, privacy policy | | `## Contact` | Contact information | Contact page, support channels |
**4. Page Entries (Required)**
Each entry follows the format: ```markdown - [Page Title](URL): Description of page content ```
Rules for page entries: - **Title:** Use the actual page title or a clear descriptive title. - **URL:** Must be a full, absolute URL (not relative paths). - **Description:** 10-30 words describing what the page covers. Be specific about the information available. - **Order:** List pages in order of importance within each section. - **Limit:** Include 10-30 page entries total. Prioritize your most authoritative and useful pages.
**5. Key Facts Section (Recommended)**
```markdown ## Key Facts - Founded in [year] by [founder(s)] - Headquarters: [City, Country] - [X] customers/users in [Y] countries - Key products: [Product A], [Product B], [Product C] - Industry: [Industry classification] ```
This section provides quick reference data that AI systems frequently need to answer user queries about your business.
**6. Contact Section (Recommended)**
```markdown ## Contact - Website: https://example.com - Email: hello@example.com - Support: support@example.com - Phone: +1-555-123-4567 - Address: 123 Main St, City, State, ZIP, Country ```
---
## llms-full.txt (Extended Version)
In addition to `llms.txt`, sites can provide `/llms-full.txt` -- an extended version with more detail.
**Differences from llms.txt:**
| Feature | llms.txt | llms-full.txt | |---|---|---| | **Length** | Concise (50-150 lines) | Comprehensive (150-500+ lines) | | **Page entries** | 10-30 key pages | 30-100+ pages | | **Descriptions** | 10-30 words per entry | 30-100 words per entry, may include key facts from each page | | **Audience** | Quick AI comprehension | Deep AI analysis | | **Sections** | 3-6 sections | 8-15 sections | | **Key facts** | Business-level facts | Page-level facts and data points |
Both files can coexist. The convention is that AI systems that choose to consult llms.txt may optionally follow the link to `llms-full.txt` for deeper detail -- but note there is no evidence (as of Aug 2026) that major AI platforms fetch either file systematically, which is why this skill frames llms.txt as a facts hedge rather than a visibility lever.
---
## Analysis Mode
When checking an existing llms.txt file:
### Step 1: Fetch the File
1. Use WebFetch to retrieve `[domain]/llms.txt`. 2. Also check for `[domain]/llms-full.txt`. 3. Record HTTP status code: - **200:** File exists -- proceed to validation. - **404:** File does not exist -- recommend generation. - **403:** File exists but is blocked -- flag as misconfiguration. - **301/302:** Redirect -- follow and note the redirect.
### Step 2: Validate Format
Check each structural element:
| Element | Check | Severity if Missing | |---|---|---| | H1 Title | Present, matches business name | Critical | | Blockquote description | Present, under 200 chars, factual | High | | At least one H2 section | Present | Critical | | Page entries with URLs | At least 5 entries present | High | | URLs are absolute | All URLs use full https:// paths | High | | URLs are valid | All URLs return 200 status | Medium | | Descriptions present | Every entry has a description after the colon | Medium | | Key Facts section | Present with business information | Medium | | Contact section | Present with at least email | Low | | Reasonable length | 30-200 lines | Low | | No broken Markdown | Proper formatting throughout | Medium |
### Step 3: Assess Content Quality
Rate the llms.txt on these dimensions:
**Completeness (0-100):** - Does it cover all major site sections visible in the navigation? - Are the most important/highest-traffic pages included? - Is the Key Facts section present with accurate business data? - Does it include recent/updated content?
**Accuracy (0-100):** - Do descriptions accurately reflect page content? - Are URLs valid and pointing to the correct pages? - Are Key Facts verifiable and current? - Is the business description accurate?
**Usefulness (0-100):** - Would an AI system understand the site's purpose from this file alone? - Are descriptions specific enough to differentiate pages? - Are the most citation-worthy pages highlighted? - Is the organization logical and intuitive?
**Overall llms.txt Score** = (Completeness * 0.40) + (Accuracy * 0.35) + (Usefulness * 0.25)
### Step 4: Compare Against Site Content
1. Crawl the site's main navigation and sitemap. 2. Identify important pages NOT listed in llms.txt. 3. Check if any listed URLs are broken or redirected. 4. Verify that the business description matches current homepage messaging. 5. Flag stale entries (pages that have been significantly updated since the llms.txt was written).
---
## Generation Mode
When creating a new llms.txt file from scratch:
**Generator script:** `skills/geo/scripts/llmstxt_generator.py` automates the crawl-and-assemble flow below. Use it as the fast path for the facts hedge -- its output is a canonical-facts file to keep AI systems from hallucinating your basics, not a ranking play. Budget ~30 minutes total including review.
### Step 1: Site Discovery
1. Fetch the homepage and extract: - Site name (from `<title>`, `<meta property="og:site_name">`, or H1) - Business description (from meta description or hero section) - Main navigation links - Footer links 2. Fetch `/sitemap.xml` to discover all public pages. 3. Identify the site's primary business type (SaaS, E-commerce, Local, Publisher, Agency).
### Step 2: Page Prioritization
Categorize all discovered pages and select the most important ones:
**Always Include:** - Homepage - About / Company page - Pricing page (if exists) - Primary product/service pages (top 3-5) - Contact page - Documentation landing page (if exists)
**Include if High Quality:** - Top blog posts (by apparent importance, recency, or comprehensiveness) - Case studies or customer stories - Key resource/guide pages - FAQ page - Careers page (for large companies)
**Skip:** - Thin category/tag pages - Pagination pages - Login/signup pages - Legal boilerplate (unless specifically relevant) - Duplicate or near-duplicate content - Pages with minimal unique content
### Step 3: Write Descriptions
For each selected page:
1. Fetch the page content using WebFetch. 2. Read the H1, meta description, and first 2-3 paragraphs. 3. Write a description that: - Is 10-30 words long - States what information is on the page - Mentions specific topics, data, or features covered - Avoids marketing language ("best," "leading," "revolutionary") - Uses factual, informative language
**Good description examples:** - `Explains the three pricing tiers (Free, Pro, Enterprise) with feature comparison and annual/monthly costs.` - `Details the company's founding in 2018, team of 45 employees, and office locations in Austin and London.` - `Covers integration setup for Slack, Salesforce, and HubSpot with step-by-step guides and API endpoints.`
**Bad description examples:** - `Our amazing pricing page!` (marketing language, no specifics) - `Learn more about our company.` (too vague) - `Click here for details.` (not descriptive)
### Step 4: Compile Key Facts
Gather key business facts from the site:
- Year founded - Founder name(s) - Headquarters location - Number of employees (if public) - Number of customers/users (if public) - Key products or services (list top 3-5) - Industry classification - Notable clients or partnerships (if public) - Key differentiators (what makes this business unique) - Recent milesto
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for geo-llmstxt, ready for a manual X post.
geo-llmstxt: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that te... 22 stars https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt?ref=x
Listing + install path for geo-llmstxt: https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt?ref=x Install: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
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Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
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@thesmokedev
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
copywriting
When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," "CTA copy," "value proposition," "tagline," "subheadline," "hero section copy," "above the fold," "this copy is weak," "make this more compelling," or "help me describe my product." Use this whenever someone is working on website text that needs to persuade or convert. For email copy, see emails. For popup copy, see popups. For editing existing copy, see copy-editing. For the offer underneath the copy (bonuses, guarantees, value framing), see offers.
46.6K Starscro
When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.
46.6K Starsrelease
Determine the next version, update the marketing site, and run the full release pipeline.
1.6K Starsdbs
dontbesilent 商业工具箱主入口。双模式:任务前路由(你的问题该用哪个 skill)+ 任务后导航(刚做完诊断,下一步该干什么)。 触发方式:/dbs、/商业、「帮我看看」、「下一步怎么走」 Main entry point for dontbesilent business toolkit. Dual mode: pre-task routing + post-task navigation. Trigger: /dbs, "help me with my business", "what's next"
Sandbox only
Install targets
Codex install prompt
Install the "geo-llmstxt" agent skill from https://github.com/TheSmokeDev/geo-skills/tree/main/skills/geo-llmstxt. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or generate new ones from scratch by crawling the site. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"thesmokedev-geo-llmstxt","task":"Install geo-llmstxt","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Maintenance
fresh
3d since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
22
60/100 Quality · 71/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Low GitHub adoption signal
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
22 GitHub stars
Repo activity
22 stars, 6 forks
Maintenance
3d since push
License
MIT
Install
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxtDo not use when
Alternative
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Alternative
46.6K Stars
npx skills add coreyhaines31/marketingskills --skill cro
Alternative
1.6K Stars
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Alternative
1.4K Stars
npx skills add Pluviobyte/rnskill --skill dbs
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/thesmokedev-geo-llmstxt/install
Agent should check
Copy prompt
Task: Use geo-llmstxt in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/thesmokedev-geo-llmstxt/install
Install command: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/thesmokedev-geo-llmstxt/install
LLM text format
/api/skills/thesmokedev-geo-llmstxt/install?format=text
Find alternatives
/api/skills/search?q=geo-llmstxt&limit=3
Agent prompt
Use geo-llmstxt for this task. Review https://www.openagentskill.com/api/skills/thesmokedev-geo-llmstxt/install, then install with: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxtRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/thesmokedev-geo-llmstxt
LLM text
/api/registry/manifest/thesmokedev-geo-llmstxt?format=text
Install alias
/api/registry/install/thesmokedev-geo-llmstxt
Recommend
/api/registry/recommend?task=Use%20geo-llmstxt%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
FIX22 GitHub stars
Stars/forks activity
FIX22 stars, 6 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Manage pipeline work
I need my agent to enrich leads, update CRM records, and prepare sales follow-ups.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Similar skills that may fit this task.
When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," "CTA copy," "value proposition," "tagline," "subheadline," "hero section copy," "above the fold," "this copy is weak," "make this more compelling," or "help me describe my product." Use this whenever someone is working on website text that needs to persuade or convert. For email copy, see emails. For popup copy, see popups. For editing existing copy, see copy-editing. For the offer underneath the copy (bonuses, guarantees, value framing), see offers.
When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.
Determine the next version, update the marketing site, and run the full release pipeline.
dontbesilent 商业工具箱主入口。双模式:任务前路由(你的问题该用哪个 skill)+ 任务后导航(刚做完诊断,下一步该干什么)。 触发方式:/dbs、/商业、「帮我看看」、「下一步怎么走」 Main entry point for dontbesilent business toolkit. Dual mode: pre-task routing + post-task navigation. Trigger: /dbs, "help me with my business", "what's next"
--- name: geo-llmstxt description: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or generate new ones from scratch by crawling the site. allowed-tools: - Read - Grep - Glob - Bash - WebFetch - Write ---
# llms.txt Standard Analysis and Generation Skill
## Purpose
This skill handles everything related to the `llms.txt` convention (proposed by Jeremy Howard in September 2024) -- a single Markdown file at the domain root that states your canonical business facts and points at your most important pages.
**Positioning as of August 2026: llms.txt is a 30-minute anti-hallucination facts hedge, NOT an AI-visibility lever.** Do not sell it to clients as a ranking or citation play -- the evidence says it does not move citations:
- **Google Search Central, 2026 (official):** "You don't need to create new machine readable files... to appear in generative AI search." Google has stated plainly that no AI-specific file is required or rewarded. - **Zyppy meta-analysis of 54 studies (via digitalapplied.com, Jun 2026):** llms.txt scores **2.0 out of 10 -- the lowest of all 23 measured GEO factors**. - **SE Ranking (seranking.com/blog/llms-txt, Nov 2025):** found **zero correlation** between having an llms.txt file and AI citation/visibility.
## What llms.txt Is Actually For
What remains is real but modest. A well-crafted llms.txt is worth roughly 30 minutes of effort because it:
1. **Reduces misrepresentation:** Key facts (pricing, features, locations, founding date) are stated explicitly in one place, reducing AI hallucination about your business when a system does consult the file. 2. **Controls the narrative:** You choose which pages and facts are presented as canonical, rather than leaving inference to a crawler. 3. **Costs almost nothing:** It is a single static Markdown file. There is no maintenance burden beyond updating it when facts change.
What it does **not** do: improve rankings, increase citation rates, or substitute for indexation, crawlability, or content quality. Treat it as hygiene -- like a favicon or a humans.txt with a purpose -- and never present it in an audit as a visibility win.
---
## The llms.txt Specification
### File Location
The file MUST be located at the root of the domain: ``` https://example.com/llms.txt ```
### Format Specification
The file uses Markdown formatting with specific conventions:
```markdown # [Site Name]
> [One-sentence description of what the site/business does. Keep under 200 characters.]
## Docs
- [Page Title](https://example.com/page-url): Concise description of what this page covers and why it matters. - [Another Page](https://example.com/another-page): Description of content.
## Optional
- [Less Critical Page](https://example.com/optional-page): Description. ```
### Detailed Format Rules
**1. Title (Required)** ```markdown # Site Name ``` - Must be the first line of the file. - Should be the official business/site name. - Use the H1 heading format (single `#`).
**2. Description (Required)** ```markdown > Brief description of the site/business ``` - Must appear immediately after the title. - Use Markdown blockquote format (`>`). - Keep under 200 characters. - Should clearly state what the business does and who it serves. - Avoid marketing fluff -- be factual and specific.
**3. Main Sections (Required -- at least one)**
Use H2 headings (`##`) to organize pages by category. Common section names:
| Section Name | Purpose | Example Content | |---|---|---| | `## Docs` | Primary documentation or key pages | Product pages, service descriptions, core content | | `## Optional` | Secondary pages worth knowing about | Blog posts, supplementary resources | | `## API` | API documentation | API reference, authentication guides | | `## Blog` | Blog or news content | Recent/popular articles | | `## Products` | Product catalog | Product pages, pricing | | `## Services` | Service offerings | Service descriptions, process pages | | `## About` | Company information | About page, team, mission | | `## Resources` | Educational/reference content | Guides, tutorials, whitepapers | | `## Legal` | Legal documents | Terms of service, privacy policy | | `## Contact` | Contact information | Contact page, support channels |
**4. Page Entries (Required)**
Each entry follows the format: ```markdown - [Page Title](URL): Description of page content ```
Rules for page entries: - **Title:** Use the actual page title or a clear descriptive title. - **URL:** Must be a full, absolute URL (not relative paths). - **Description:** 10-30 words describing what the page covers. Be specific about the information available. - **Order:** List pages in order of importance within each section. - **Limit:** Include 10-30 page entries total. Prioritize your most authoritative and useful pages.
**5. Key Facts Section (Recommended)**
```markdown ## Key Facts - Founded in [year] by [founder(s)] - Headquarters: [City, Country] - [X] customers/users in [Y] countries - Key products: [Product A], [Product B], [Product C] - Industry: [Industry classification] ```
This section provides quick reference data that AI systems frequently need to answer user queries about your business.
**6. Contact Section (Recommended)**
```markdown ## Contact - Website: https://example.com - Email: hello@example.com - Support: support@example.com - Phone: +1-555-123-4567 - Address: 123 Main St, City, State, ZIP, Country ```
---
## llms-full.txt (Extended Version)
In addition to `llms.txt`, sites can provide `/llms-full.txt` -- an extended version with more detail.
**Differences from llms.txt:**
| Feature | llms.txt | llms-full.txt | |---|---|---| | **Length** | Concise (50-150 lines) | Comprehensive (150-500+ lines) | | **Page entries** | 10-30 key pages | 30-100+ pages | | **Descriptions** | 10-30 words per entry | 30-100 words per entry, may include key facts from each page | | **Audience** | Quick AI comprehension | Deep AI analysis | | **Sections** | 3-6 sections | 8-15 sections | | **Key facts** | Business-level facts | Page-level facts and data points |
Both files can coexist. The convention is that AI systems that choose to consult llms.txt may optionally follow the link to `llms-full.txt` for deeper detail -- but note there is no evidence (as of Aug 2026) that major AI platforms fetch either file systematically, which is why this skill frames llms.txt as a facts hedge rather than a visibility lever.
---
## Analysis Mode
When checking an existing llms.txt file:
### Step 1: Fetch the File
1. Use WebFetch to retrieve `[domain]/llms.txt`. 2. Also check for `[domain]/llms-full.txt`. 3. Record HTTP status code: - **200:** File exists -- proceed to validation. - **404:** File does not exist -- recommend generation. - **403:** File exists but is blocked -- flag as misconfiguration. - **301/302:** Redirect -- follow and note the redirect.
### Step 2: Validate Format
Check each structural element:
| Element | Check | Severity if Missing | |---|---|---| | H1 Title | Present, matches business name | Critical | | Blockquote description | Present, under 200 chars, factual | High | | At least one H2 section | Present | Critical | | Page entries with URLs | At least 5 entries present | High | | URLs are absolute | All URLs use full https:// paths | High | | URLs are valid | All URLs return 200 status | Medium | | Descriptions present | Every entry has a description after the colon | Medium | | Key Facts section | Present with business information | Medium | | Contact section | Present with at least email | Low | | Reasonable length | 30-200 lines | Low | | No broken Markdown | Proper formatting throughout | Medium |
### Step 3: Assess Content Quality
Rate the llms.txt on these dimensions:
**Completeness (0-100):** - Does it cover all major site sections visible in the navigation? - Are the most important/highest-traffic pages included? - Is the Key Facts section present with accurate business data? - Does it include recent/updated content?
**Accuracy (0-100):** - Do descriptions accurately reflect page content? - Are URLs valid and pointing to the correct pages? - Are Key Facts verifiable and current? - Is the business description accurate?
**Usefulness (0-100):** - Would an AI system understand the site's purpose from this file alone? - Are descriptions specific enough to differentiate pages? - Are the most citation-worthy pages highlighted? - Is the organization logical and intuitive?
**Overall llms.txt Score** = (Completeness * 0.40) + (Accuracy * 0.35) + (Usefulness * 0.25)
### Step 4: Compare Against Site Content
1. Crawl the site's main navigation and sitemap. 2. Identify important pages NOT listed in llms.txt. 3. Check if any listed URLs are broken or redirected. 4. Verify that the business description matches current homepage messaging. 5. Flag stale entries (pages that have been significantly updated since the llms.txt was written).
---
## Generation Mode
When creating a new llms.txt file from scratch:
**Generator script:** `skills/geo/scripts/llmstxt_generator.py` automates the crawl-and-assemble flow below. Use it as the fast path for the facts hedge -- its output is a canonical-facts file to keep AI systems from hallucinating your basics, not a ranking play. Budget ~30 minutes total including review.
### Step 1: Site Discovery
1. Fetch the homepage and extract: - Site name (from `<title>`, `<meta property="og:site_name">`, or H1) - Business description (from meta description or hero section) - Main navigation links - Footer links 2. Fetch `/sitemap.xml` to discover all public pages. 3. Identify the site's primary business type (SaaS, E-commerce, Local, Publisher, Agency).
### Step 2: Page Prioritization
Categorize all discovered pages and select the most important ones:
**Always Include:** - Homepage - About / Company page - Pricing page (if exists) - Primary product/service pages (top 3-5) - Contact page - Documentation landing page (if exists)
**Include if High Quality:** - Top blog posts (by apparent importance, recency, or comprehensiveness) - Case studies or customer stories - Key resource/guide pages - FAQ page - Careers page (for large companies)
**Skip:** - Thin category/tag pages - Pagination pages - Login/signup pages - Legal boilerplate (unless specifically relevant) - Duplicate or near-duplicate content - Pages with minimal unique content
### Step 3: Write Descriptions
For each selected page:
1. Fetch the page content using WebFetch. 2. Read the H1, meta description, and first 2-3 paragraphs. 3. Write a description that: - Is 10-30 words long - States what information is on the page - Mentions specific topics, data, or features covered - Avoids marketing language ("best," "leading," "revolutionary") - Uses factual, informative language
**Good description examples:** - `Explains the three pricing tiers (Free, Pro, Enterprise) with feature comparison and annual/monthly costs.` - `Details the company's founding in 2018, team of 45 employees, and office locations in Austin and London.` - `Covers integration setup for Slack, Salesforce, and HubSpot with step-by-step guides and API endpoints.`
**Bad description examples:** - `Our amazing pricing page!` (marketing language, no specifics) - `Learn more about our company.` (too vague) - `Click here for details.` (not descriptive)
### Step 4: Compile Key Facts
Gather key business facts from the site:
- Year founded - Founder name(s) - Headquarters location - Number of employees (if public) - Number of customers/users (if public) - Key products or services (list top 3-5) - Industry classification - Notable clients or partnerships (if public) - Key differentiators (what makes this business unique) - Recent milesto
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for geo-llmstxt, ready for a manual X post.
geo-llmstxt: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that te... 22 stars https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt?ref=x
Listing + install path for geo-llmstxt: https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt?ref=x Install: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to TheSmokeDev but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
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[](https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt/audit)
[](https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)TheSmokeDev
@thesmokedev
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
copywriting
When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," "CTA copy," "value proposition," "tagline," "subheadline," "hero section copy," "above the fold," "this copy is weak," "make this more compelling," or "help me describe my product." Use this whenever someone is working on website text that needs to persuade or convert. For email copy, see emails. For popup copy, see popups. For editing existing copy, see copy-editing. For the offer underneath the copy (bonuses, guarantees, value framing), see offers.
46.6K Starscro
When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.
46.6K Starsrelease
Determine the next version, update the marketing site, and run the full release pipeline.
1.6K Starsdbs
dontbesilent 商业工具箱主入口。双模式:任务前路由(你的问题该用哪个 skill)+ 任务后导航(刚做完诊断,下一步该干什么)。 触发方式:/dbs、/商业、「帮我看看」、「下一步怎么走」 Main entry point for dontbesilent business toolkit. Dual mode: pre-task routing + post-task navigation. Trigger: /dbs, "help me with my business", "what's next"
Sandbox only
Install targets
Codex install prompt
Install the "geo-llmstxt" agent skill from https://github.com/TheSmokeDev/geo-skills/tree/main/skills/geo-llmstxt. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or generate new ones from scratch by crawling the site. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"thesmokedev-geo-llmstxt","task":"Install geo-llmstxt","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Maintenance
fresh
3d since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
22
60/100 Quality · 71/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Low GitHub adoption signal
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
22 GitHub stars
Repo activity
22 stars, 6 forks
Maintenance
3d since push
License
MIT
Install
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxtDo not use when
Alternative
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Alternative
46.6K Stars
npx skills add coreyhaines31/marketingskills --skill cro
Alternative
1.6K Stars
npx skills add Shpigford/chops --skill release
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1.4K Stars
npx skills add Pluviobyte/rnskill --skill dbs
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/thesmokedev-geo-llmstxt/install
Agent should check
Copy prompt
Task: Use geo-llmstxt in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/thesmokedev-geo-llmstxt/install
Install command: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/thesmokedev-geo-llmstxt/install
LLM text format
/api/skills/thesmokedev-geo-llmstxt/install?format=text
Find alternatives
/api/skills/search?q=geo-llmstxt&limit=3
Agent prompt
Use geo-llmstxt for this task. Review https://www.openagentskill.com/api/skills/thesmokedev-geo-llmstxt/install, then install with: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxtRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/thesmokedev-geo-llmstxt
LLM text
/api/registry/manifest/thesmokedev-geo-llmstxt?format=text
Install alias
/api/registry/install/thesmokedev-geo-llmstxt
Recommend
/api/registry/recommend?task=Use%20geo-llmstxt%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
FIX22 GitHub stars
Stars/forks activity
FIX22 stars, 6 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Manage pipeline work
I need my agent to enrich leads, update CRM records, and prepare sales follow-ups.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Similar skills that may fit this task.
When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," "CTA copy," "value proposition," "tagline," "subheadline," "hero section copy," "above the fold," "this copy is weak," "make this more compelling," or "help me describe my product." Use this whenever someone is working on website text that needs to persuade or convert. For email copy, see emails. For popup copy, see popups. For editing existing copy, see copy-editing. For the offer underneath the copy (bonuses, guarantees, value framing), see offers.
When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.
Determine the next version, update the marketing site, and run the full release pipeline.
dontbesilent 商业工具箱主入口。双模式:任务前路由(你的问题该用哪个 skill)+ 任务后导航(刚做完诊断,下一步该干什么)。 触发方式:/dbs、/商业、「帮我看看」、「下一步怎么走」 Main entry point for dontbesilent business toolkit. Dual mode: pre-task routing + post-task navigation. Trigger: /dbs, "help me with my business", "what's next"
--- name: geo-llmstxt description: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or generate new ones from scratch by crawling the site. allowed-tools: - Read - Grep - Glob - Bash - WebFetch - Write ---
# llms.txt Standard Analysis and Generation Skill
## Purpose
This skill handles everything related to the `llms.txt` convention (proposed by Jeremy Howard in September 2024) -- a single Markdown file at the domain root that states your canonical business facts and points at your most important pages.
**Positioning as of August 2026: llms.txt is a 30-minute anti-hallucination facts hedge, NOT an AI-visibility lever.** Do not sell it to clients as a ranking or citation play -- the evidence says it does not move citations:
- **Google Search Central, 2026 (official):** "You don't need to create new machine readable files... to appear in generative AI search." Google has stated plainly that no AI-specific file is required or rewarded. - **Zyppy meta-analysis of 54 studies (via digitalapplied.com, Jun 2026):** llms.txt scores **2.0 out of 10 -- the lowest of all 23 measured GEO factors**. - **SE Ranking (seranking.com/blog/llms-txt, Nov 2025):** found **zero correlation** between having an llms.txt file and AI citation/visibility.
## What llms.txt Is Actually For
What remains is real but modest. A well-crafted llms.txt is worth roughly 30 minutes of effort because it:
1. **Reduces misrepresentation:** Key facts (pricing, features, locations, founding date) are stated explicitly in one place, reducing AI hallucination about your business when a system does consult the file. 2. **Controls the narrative:** You choose which pages and facts are presented as canonical, rather than leaving inference to a crawler. 3. **Costs almost nothing:** It is a single static Markdown file. There is no maintenance burden beyond updating it when facts change.
What it does **not** do: improve rankings, increase citation rates, or substitute for indexation, crawlability, or content quality. Treat it as hygiene -- like a favicon or a humans.txt with a purpose -- and never present it in an audit as a visibility win.
---
## The llms.txt Specification
### File Location
The file MUST be located at the root of the domain: ``` https://example.com/llms.txt ```
### Format Specification
The file uses Markdown formatting with specific conventions:
```markdown # [Site Name]
> [One-sentence description of what the site/business does. Keep under 200 characters.]
## Docs
- [Page Title](https://example.com/page-url): Concise description of what this page covers and why it matters. - [Another Page](https://example.com/another-page): Description of content.
## Optional
- [Less Critical Page](https://example.com/optional-page): Description. ```
### Detailed Format Rules
**1. Title (Required)** ```markdown # Site Name ``` - Must be the first line of the file. - Should be the official business/site name. - Use the H1 heading format (single `#`).
**2. Description (Required)** ```markdown > Brief description of the site/business ``` - Must appear immediately after the title. - Use Markdown blockquote format (`>`). - Keep under 200 characters. - Should clearly state what the business does and who it serves. - Avoid marketing fluff -- be factual and specific.
**3. Main Sections (Required -- at least one)**
Use H2 headings (`##`) to organize pages by category. Common section names:
| Section Name | Purpose | Example Content | |---|---|---| | `## Docs` | Primary documentation or key pages | Product pages, service descriptions, core content | | `## Optional` | Secondary pages worth knowing about | Blog posts, supplementary resources | | `## API` | API documentation | API reference, authentication guides | | `## Blog` | Blog or news content | Recent/popular articles | | `## Products` | Product catalog | Product pages, pricing | | `## Services` | Service offerings | Service descriptions, process pages | | `## About` | Company information | About page, team, mission | | `## Resources` | Educational/reference content | Guides, tutorials, whitepapers | | `## Legal` | Legal documents | Terms of service, privacy policy | | `## Contact` | Contact information | Contact page, support channels |
**4. Page Entries (Required)**
Each entry follows the format: ```markdown - [Page Title](URL): Description of page content ```
Rules for page entries: - **Title:** Use the actual page title or a clear descriptive title. - **URL:** Must be a full, absolute URL (not relative paths). - **Description:** 10-30 words describing what the page covers. Be specific about the information available. - **Order:** List pages in order of importance within each section. - **Limit:** Include 10-30 page entries total. Prioritize your most authoritative and useful pages.
**5. Key Facts Section (Recommended)**
```markdown ## Key Facts - Founded in [year] by [founder(s)] - Headquarters: [City, Country] - [X] customers/users in [Y] countries - Key products: [Product A], [Product B], [Product C] - Industry: [Industry classification] ```
This section provides quick reference data that AI systems frequently need to answer user queries about your business.
**6. Contact Section (Recommended)**
```markdown ## Contact - Website: https://example.com - Email: hello@example.com - Support: support@example.com - Phone: +1-555-123-4567 - Address: 123 Main St, City, State, ZIP, Country ```
---
## llms-full.txt (Extended Version)
In addition to `llms.txt`, sites can provide `/llms-full.txt` -- an extended version with more detail.
**Differences from llms.txt:**
| Feature | llms.txt | llms-full.txt | |---|---|---| | **Length** | Concise (50-150 lines) | Comprehensive (150-500+ lines) | | **Page entries** | 10-30 key pages | 30-100+ pages | | **Descriptions** | 10-30 words per entry | 30-100 words per entry, may include key facts from each page | | **Audience** | Quick AI comprehension | Deep AI analysis | | **Sections** | 3-6 sections | 8-15 sections | | **Key facts** | Business-level facts | Page-level facts and data points |
Both files can coexist. The convention is that AI systems that choose to consult llms.txt may optionally follow the link to `llms-full.txt` for deeper detail -- but note there is no evidence (as of Aug 2026) that major AI platforms fetch either file systematically, which is why this skill frames llms.txt as a facts hedge rather than a visibility lever.
---
## Analysis Mode
When checking an existing llms.txt file:
### Step 1: Fetch the File
1. Use WebFetch to retrieve `[domain]/llms.txt`. 2. Also check for `[domain]/llms-full.txt`. 3. Record HTTP status code: - **200:** File exists -- proceed to validation. - **404:** File does not exist -- recommend generation. - **403:** File exists but is blocked -- flag as misconfiguration. - **301/302:** Redirect -- follow and note the redirect.
### Step 2: Validate Format
Check each structural element:
| Element | Check | Severity if Missing | |---|---|---| | H1 Title | Present, matches business name | Critical | | Blockquote description | Present, under 200 chars, factual | High | | At least one H2 section | Present | Critical | | Page entries with URLs | At least 5 entries present | High | | URLs are absolute | All URLs use full https:// paths | High | | URLs are valid | All URLs return 200 status | Medium | | Descriptions present | Every entry has a description after the colon | Medium | | Key Facts section | Present with business information | Medium | | Contact section | Present with at least email | Low | | Reasonable length | 30-200 lines | Low | | No broken Markdown | Proper formatting throughout | Medium |
### Step 3: Assess Content Quality
Rate the llms.txt on these dimensions:
**Completeness (0-100):** - Does it cover all major site sections visible in the navigation? - Are the most important/highest-traffic pages included? - Is the Key Facts section present with accurate business data? - Does it include recent/updated content?
**Accuracy (0-100):** - Do descriptions accurately reflect page content? - Are URLs valid and pointing to the correct pages? - Are Key Facts verifiable and current? - Is the business description accurate?
**Usefulness (0-100):** - Would an AI system understand the site's purpose from this file alone? - Are descriptions specific enough to differentiate pages? - Are the most citation-worthy pages highlighted? - Is the organization logical and intuitive?
**Overall llms.txt Score** = (Completeness * 0.40) + (Accuracy * 0.35) + (Usefulness * 0.25)
### Step 4: Compare Against Site Content
1. Crawl the site's main navigation and sitemap. 2. Identify important pages NOT listed in llms.txt. 3. Check if any listed URLs are broken or redirected. 4. Verify that the business description matches current homepage messaging. 5. Flag stale entries (pages that have been significantly updated since the llms.txt was written).
---
## Generation Mode
When creating a new llms.txt file from scratch:
**Generator script:** `skills/geo/scripts/llmstxt_generator.py` automates the crawl-and-assemble flow below. Use it as the fast path for the facts hedge -- its output is a canonical-facts file to keep AI systems from hallucinating your basics, not a ranking play. Budget ~30 minutes total including review.
### Step 1: Site Discovery
1. Fetch the homepage and extract: - Site name (from `<title>`, `<meta property="og:site_name">`, or H1) - Business description (from meta description or hero section) - Main navigation links - Footer links 2. Fetch `/sitemap.xml` to discover all public pages. 3. Identify the site's primary business type (SaaS, E-commerce, Local, Publisher, Agency).
### Step 2: Page Prioritization
Categorize all discovered pages and select the most important ones:
**Always Include:** - Homepage - About / Company page - Pricing page (if exists) - Primary product/service pages (top 3-5) - Contact page - Documentation landing page (if exists)
**Include if High Quality:** - Top blog posts (by apparent importance, recency, or comprehensiveness) - Case studies or customer stories - Key resource/guide pages - FAQ page - Careers page (for large companies)
**Skip:** - Thin category/tag pages - Pagination pages - Login/signup pages - Legal boilerplate (unless specifically relevant) - Duplicate or near-duplicate content - Pages with minimal unique content
### Step 3: Write Descriptions
For each selected page:
1. Fetch the page content using WebFetch. 2. Read the H1, meta description, and first 2-3 paragraphs. 3. Write a description that: - Is 10-30 words long - States what information is on the page - Mentions specific topics, data, or features covered - Avoids marketing language ("best," "leading," "revolutionary") - Uses factual, informative language
**Good description examples:** - `Explains the three pricing tiers (Free, Pro, Enterprise) with feature comparison and annual/monthly costs.` - `Details the company's founding in 2018, team of 45 employees, and office locations in Austin and London.` - `Covers integration setup for Slack, Salesforce, and HubSpot with step-by-step guides and API endpoints.`
**Bad description examples:** - `Our amazing pricing page!` (marketing language, no specifics) - `Learn more about our company.` (too vague) - `Click here for details.` (not descriptive)
### Step 4: Compile Key Facts
Gather key business facts from the site:
- Year founded - Founder name(s) - Headquarters location - Number of employees (if public) - Number of customers/users (if public) - Key products or services (list top 3-5) - Industry classification - Notable clients or partnerships (if public) - Key differentiators (what makes this business unique) - Recent milesto
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for geo-llmstxt, ready for a manual X post.
geo-llmstxt: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that te... 22 stars https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt?ref=x
Listing + install path for geo-llmstxt: https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt?ref=x Install: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
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copywriting
When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," "CTA copy," "value proposition," "tagline," "subheadline," "hero section copy," "above the fold," "this copy is weak," "make this more compelling," or "help me describe my product." Use this whenever someone is working on website text that needs to persuade or convert. For email copy, see emails. For popup copy, see popups. For editing existing copy, see copy-editing. For the offer underneath the copy (bonuses, guarantees, value framing), see offers.
46.6K Starscro
When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.
46.6K Starsrelease
Determine the next version, update the marketing site, and run the full release pipeline.
1.6K Starsdbs
dontbesilent 商业工具箱主入口。双模式:任务前路由(你的问题该用哪个 skill)+ 任务后导航(刚做完诊断,下一步该干什么)。 触发方式:/dbs、/商业、「帮我看看」、「下一步怎么走」 Main entry point for dontbesilent business toolkit. Dual mode: pre-task routing + post-task navigation. Trigger: /dbs, "help me with my business", "what's next"
Sandbox only
Install targets
Codex install prompt
Install the "geo-llmstxt" agent skill from https://github.com/TheSmokeDev/geo-skills/tree/main/skills/geo-llmstxt. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or generate new ones from scratch by crawling the site. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"thesmokedev-geo-llmstxt","task":"Install geo-llmstxt","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Maintenance
fresh
3d since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
22
60/100 Quality · 71/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Low GitHub adoption signal
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
22 GitHub stars
Repo activity
22 stars, 6 forks
Maintenance
3d since push
License
MIT
Install
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add TheSmokeDev/geo-skills --skill geo-llmstxtDo not use when
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npx skills add coreyhaines31/marketingskills --skill copywriting
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npx skills add coreyhaines31/marketingskills --skill cro
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npx skills add Shpigford/chops --skill release
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npx skills add Pluviobyte/rnskill --skill dbs
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/thesmokedev-geo-llmstxt/install
Agent should check
Copy prompt
Task: Use geo-llmstxt in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20geo-llmstxt%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/thesmokedev-geo-llmstxt/install
Install command: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/thesmokedev-geo-llmstxt/install
LLM text format
/api/skills/thesmokedev-geo-llmstxt/install?format=text
Find alternatives
/api/skills/search?q=geo-llmstxt&limit=3
Agent prompt
Use geo-llmstxt for this task. Review https://www.openagentskill.com/api/skills/thesmokedev-geo-llmstxt/install, then install with: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxtRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/thesmokedev-geo-llmstxt
LLM text
/api/registry/manifest/thesmokedev-geo-llmstxt?format=text
Install alias
/api/registry/install/thesmokedev-geo-llmstxt
Recommend
/api/registry/recommend?task=Use%20geo-llmstxt%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
FIX22 GitHub stars
Stars/forks activity
FIX22 stars, 6 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Manage pipeline work
I need my agent to enrich leads, update CRM records, and prepare sales follow-ups.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Scrape, clean, and reuse web data
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Similar skills that may fit this task.
When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," "CTA copy," "value proposition," "tagline," "subheadline," "hero section copy," "above the fold," "this copy is weak," "make this more compelling," or "help me describe my product." Use this whenever someone is working on website text that needs to persuade or convert. For email copy, see emails. For popup copy, see popups. For editing existing copy, see copy-editing. For the offer underneath the copy (bonuses, guarantees, value framing), see offers.
When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.
Determine the next version, update the marketing site, and run the full release pipeline.
dontbesilent 商业工具箱主入口。双模式:任务前路由(你的问题该用哪个 skill)+ 任务后导航(刚做完诊断,下一步该干什么)。 触发方式:/dbs、/商业、「帮我看看」、「下一步怎么走」 Main entry point for dontbesilent business toolkit. Dual mode: pre-task routing + post-task navigation. Trigger: /dbs, "help me with my business", "what's next"
--- name: geo-llmstxt description: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that tells AI systems your canonical business facts and key pages. NOT an AI-visibility or citation lever (debunked by Google, Zyppy, and SE Ranking). Can validate existing llms.txt files or generate new ones from scratch by crawling the site. allowed-tools: - Read - Grep - Glob - Bash - WebFetch - Write ---
# llms.txt Standard Analysis and Generation Skill
## Purpose
This skill handles everything related to the `llms.txt` convention (proposed by Jeremy Howard in September 2024) -- a single Markdown file at the domain root that states your canonical business facts and points at your most important pages.
**Positioning as of August 2026: llms.txt is a 30-minute anti-hallucination facts hedge, NOT an AI-visibility lever.** Do not sell it to clients as a ranking or citation play -- the evidence says it does not move citations:
- **Google Search Central, 2026 (official):** "You don't need to create new machine readable files... to appear in generative AI search." Google has stated plainly that no AI-specific file is required or rewarded. - **Zyppy meta-analysis of 54 studies (via digitalapplied.com, Jun 2026):** llms.txt scores **2.0 out of 10 -- the lowest of all 23 measured GEO factors**. - **SE Ranking (seranking.com/blog/llms-txt, Nov 2025):** found **zero correlation** between having an llms.txt file and AI citation/visibility.
## What llms.txt Is Actually For
What remains is real but modest. A well-crafted llms.txt is worth roughly 30 minutes of effort because it:
1. **Reduces misrepresentation:** Key facts (pricing, features, locations, founding date) are stated explicitly in one place, reducing AI hallucination about your business when a system does consult the file. 2. **Controls the narrative:** You choose which pages and facts are presented as canonical, rather than leaving inference to a crawler. 3. **Costs almost nothing:** It is a single static Markdown file. There is no maintenance burden beyond updating it when facts change.
What it does **not** do: improve rankings, increase citation rates, or substitute for indexation, crawlability, or content quality. Treat it as hygiene -- like a favicon or a humans.txt with a purpose -- and never present it in an audit as a visibility win.
---
## The llms.txt Specification
### File Location
The file MUST be located at the root of the domain: ``` https://example.com/llms.txt ```
### Format Specification
The file uses Markdown formatting with specific conventions:
```markdown # [Site Name]
> [One-sentence description of what the site/business does. Keep under 200 characters.]
## Docs
- [Page Title](https://example.com/page-url): Concise description of what this page covers and why it matters. - [Another Page](https://example.com/another-page): Description of content.
## Optional
- [Less Critical Page](https://example.com/optional-page): Description. ```
### Detailed Format Rules
**1. Title (Required)** ```markdown # Site Name ``` - Must be the first line of the file. - Should be the official business/site name. - Use the H1 heading format (single `#`).
**2. Description (Required)** ```markdown > Brief description of the site/business ``` - Must appear immediately after the title. - Use Markdown blockquote format (`>`). - Keep under 200 characters. - Should clearly state what the business does and who it serves. - Avoid marketing fluff -- be factual and specific.
**3. Main Sections (Required -- at least one)**
Use H2 headings (`##`) to organize pages by category. Common section names:
| Section Name | Purpose | Example Content | |---|---|---| | `## Docs` | Primary documentation or key pages | Product pages, service descriptions, core content | | `## Optional` | Secondary pages worth knowing about | Blog posts, supplementary resources | | `## API` | API documentation | API reference, authentication guides | | `## Blog` | Blog or news content | Recent/popular articles | | `## Products` | Product catalog | Product pages, pricing | | `## Services` | Service offerings | Service descriptions, process pages | | `## About` | Company information | About page, team, mission | | `## Resources` | Educational/reference content | Guides, tutorials, whitepapers | | `## Legal` | Legal documents | Terms of service, privacy policy | | `## Contact` | Contact information | Contact page, support channels |
**4. Page Entries (Required)**
Each entry follows the format: ```markdown - [Page Title](URL): Description of page content ```
Rules for page entries: - **Title:** Use the actual page title or a clear descriptive title. - **URL:** Must be a full, absolute URL (not relative paths). - **Description:** 10-30 words describing what the page covers. Be specific about the information available. - **Order:** List pages in order of importance within each section. - **Limit:** Include 10-30 page entries total. Prioritize your most authoritative and useful pages.
**5. Key Facts Section (Recommended)**
```markdown ## Key Facts - Founded in [year] by [founder(s)] - Headquarters: [City, Country] - [X] customers/users in [Y] countries - Key products: [Product A], [Product B], [Product C] - Industry: [Industry classification] ```
This section provides quick reference data that AI systems frequently need to answer user queries about your business.
**6. Contact Section (Recommended)**
```markdown ## Contact - Website: https://example.com - Email: hello@example.com - Support: support@example.com - Phone: +1-555-123-4567 - Address: 123 Main St, City, State, ZIP, Country ```
---
## llms-full.txt (Extended Version)
In addition to `llms.txt`, sites can provide `/llms-full.txt` -- an extended version with more detail.
**Differences from llms.txt:**
| Feature | llms.txt | llms-full.txt | |---|---|---| | **Length** | Concise (50-150 lines) | Comprehensive (150-500+ lines) | | **Page entries** | 10-30 key pages | 30-100+ pages | | **Descriptions** | 10-30 words per entry | 30-100 words per entry, may include key facts from each page | | **Audience** | Quick AI comprehension | Deep AI analysis | | **Sections** | 3-6 sections | 8-15 sections | | **Key facts** | Business-level facts | Page-level facts and data points |
Both files can coexist. The convention is that AI systems that choose to consult llms.txt may optionally follow the link to `llms-full.txt` for deeper detail -- but note there is no evidence (as of Aug 2026) that major AI platforms fetch either file systematically, which is why this skill frames llms.txt as a facts hedge rather than a visibility lever.
---
## Analysis Mode
When checking an existing llms.txt file:
### Step 1: Fetch the File
1. Use WebFetch to retrieve `[domain]/llms.txt`. 2. Also check for `[domain]/llms-full.txt`. 3. Record HTTP status code: - **200:** File exists -- proceed to validation. - **404:** File does not exist -- recommend generation. - **403:** File exists but is blocked -- flag as misconfiguration. - **301/302:** Redirect -- follow and note the redirect.
### Step 2: Validate Format
Check each structural element:
| Element | Check | Severity if Missing | |---|---|---| | H1 Title | Present, matches business name | Critical | | Blockquote description | Present, under 200 chars, factual | High | | At least one H2 section | Present | Critical | | Page entries with URLs | At least 5 entries present | High | | URLs are absolute | All URLs use full https:// paths | High | | URLs are valid | All URLs return 200 status | Medium | | Descriptions present | Every entry has a description after the colon | Medium | | Key Facts section | Present with business information | Medium | | Contact section | Present with at least email | Low | | Reasonable length | 30-200 lines | Low | | No broken Markdown | Proper formatting throughout | Medium |
### Step 3: Assess Content Quality
Rate the llms.txt on these dimensions:
**Completeness (0-100):** - Does it cover all major site sections visible in the navigation? - Are the most important/highest-traffic pages included? - Is the Key Facts section present with accurate business data? - Does it include recent/updated content?
**Accuracy (0-100):** - Do descriptions accurately reflect page content? - Are URLs valid and pointing to the correct pages? - Are Key Facts verifiable and current? - Is the business description accurate?
**Usefulness (0-100):** - Would an AI system understand the site's purpose from this file alone? - Are descriptions specific enough to differentiate pages? - Are the most citation-worthy pages highlighted? - Is the organization logical and intuitive?
**Overall llms.txt Score** = (Completeness * 0.40) + (Accuracy * 0.35) + (Usefulness * 0.25)
### Step 4: Compare Against Site Content
1. Crawl the site's main navigation and sitemap. 2. Identify important pages NOT listed in llms.txt. 3. Check if any listed URLs are broken or redirected. 4. Verify that the business description matches current homepage messaging. 5. Flag stale entries (pages that have been significantly updated since the llms.txt was written).
---
## Generation Mode
When creating a new llms.txt file from scratch:
**Generator script:** `skills/geo/scripts/llmstxt_generator.py` automates the crawl-and-assemble flow below. Use it as the fast path for the facts hedge -- its output is a canonical-facts file to keep AI systems from hallucinating your basics, not a ranking play. Budget ~30 minutes total including review.
### Step 1: Site Discovery
1. Fetch the homepage and extract: - Site name (from `<title>`, `<meta property="og:site_name">`, or H1) - Business description (from meta description or hero section) - Main navigation links - Footer links 2. Fetch `/sitemap.xml` to discover all public pages. 3. Identify the site's primary business type (SaaS, E-commerce, Local, Publisher, Agency).
### Step 2: Page Prioritization
Categorize all discovered pages and select the most important ones:
**Always Include:** - Homepage - About / Company page - Pricing page (if exists) - Primary product/service pages (top 3-5) - Contact page - Documentation landing page (if exists)
**Include if High Quality:** - Top blog posts (by apparent importance, recency, or comprehensiveness) - Case studies or customer stories - Key resource/guide pages - FAQ page - Careers page (for large companies)
**Skip:** - Thin category/tag pages - Pagination pages - Login/signup pages - Legal boilerplate (unless specifically relevant) - Duplicate or near-duplicate content - Pages with minimal unique content
### Step 3: Write Descriptions
For each selected page:
1. Fetch the page content using WebFetch. 2. Read the H1, meta description, and first 2-3 paragraphs. 3. Write a description that: - Is 10-30 words long - States what information is on the page - Mentions specific topics, data, or features covered - Avoids marketing language ("best," "leading," "revolutionary") - Uses factual, informative language
**Good description examples:** - `Explains the three pricing tiers (Free, Pro, Enterprise) with feature comparison and annual/monthly costs.` - `Details the company's founding in 2018, team of 45 employees, and office locations in Austin and London.` - `Covers integration setup for Slack, Salesforce, and HubSpot with step-by-step guides and API endpoints.`
**Bad description examples:** - `Our amazing pricing page!` (marketing language, no specifics) - `Learn more about our company.` (too vague) - `Click here for details.` (not descriptive)
### Step 4: Compile Key Facts
Gather key business facts from the site:
- Year founded - Founder name(s) - Headquarters location - Number of employees (if public) - Number of customers/users (if public) - Key products or services (list top 3-5) - Industry classification - Notable clients or partnerships (if public) - Key differentiators (what makes this business unique) - Recent milesto
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geo-llmstxt: Analyzes and generates llms.txt files -- a lightweight anti-hallucination facts hedge that te... 22 stars https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt?ref=x
Listing + install path for geo-llmstxt: https://www.openagentskill.com/skills/thesmokedev-geo-llmstxt?ref=x Install: npx skills add TheSmokeDev/geo-skills --skill geo-llmstxt
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copywriting
When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," "CTA copy," "value proposition," "tagline," "subheadline," "hero section copy," "above the fold," "this copy is weak," "make this more compelling," or "help me describe my product." Use this whenever someone is working on website text that needs to persuade or convert. For email copy, see emails. For popup copy, see popups. For editing existing copy, see copy-editing. For the offer underneath the copy (bonuses, guarantees, value framing), see offers.
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When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.
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Determine the next version, update the marketing site, and run the full release pipeline.
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dontbesilent 商业工具箱主入口。双模式:任务前路由(你的问题该用哪个 skill)+ 任务后导航(刚做完诊断,下一步该干什么)。 触发方式:/dbs、/商业、「帮我看看」、「下一步怎么走」 Main entry point for dontbesilent business toolkit. Dual mode: pre-task routing + post-task navigation. Trigger: /dbs, "help me with my business", "what's next"
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shell or command execution, filesystem or document access
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Docs
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Install readiness
Permission surface
shell or command execution, filesystem or document access
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Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
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Docs
Strong README/SKILL.md context
Risk summary
Install readiness