Indexé dans Registry

llm-friendly-site-architect

Prix non confirmé★ 39 Stars GitHubRegistre mis à jour · 10 sept. 2026agent-skill

Vue d’ensemble

Design human-visible, machine-readable website layers for AI assistants, RAG, and agentic search. Use this skill when the user asks for llms.txt, LLM discovery plans, visible TLDR or direct-answer blocks, source trails, entity pages, markdown alternates, AI crawler policy, topic-to-URL maps, assistant-readable public content, or LLM-friendly architecture that must preserve canonical SEO strategy without hidden bot-only facts or duplicate story bodies.

Lire la documentation complète

Documentation source, pas des instructions pour ce site. Vérifiez les permissions avant d’exécuter des commandes.

LLM Friendly Site Architect

Use this skill after semantic core, URL architecture, internal link graph, and technical SEO/schema foundations exist.

Read references/llm-readable-architecture.md before producing a full LLM discovery plan.

Owns

llms.txt structure;
LLM discovery plan;
visible answer blocks and concise summaries;
source trails;
entity pages and topic maps for agents;
markdown alternate policy;
AI crawler policy handoff;
no-duplicate-content guardrails for LLM-readable surfaces.

Does Not Own

Search Console or assistant citation monitoring execution;
technical schema implementation;
URL/canonical decisions;
hidden content;
external authority placement.

Workflow

Read url-map.yaml, internal-link-graph.yaml, schema/head policy, and visible content model.
Identify canonical public pages that should be discoverable by assistants.
Draft or audit llms.txt sections with only public useful URLs.
Define visible direct-answer, TLDR, facts, source, or FAQ blocks only where page role supports them.
Define source-trail and citation-ready evidence surfaces.
Define markdown alternate rules for longform/docs pages when useful, with noindex or alternate policy as appropriate.
Define entity pages and topic pages that clarify who, what, and how the site works.
Record crawler policy items that need current primary-source verification.
Produce an LLM discovery report using assets/llm-discovery-report.template.md.

Non-Negotiables

Human-visible content first.
No hidden bot-only facts.
No doorway pages.
No FAQPage schema unless FAQ is visible.
No automatic TLDR on every short news page by default.
No extra public story bodies beyond the declared content model.
llms.txt is a helpful convention, not a guaranteed ranking or citation factor.
Crawler names, policies, and IPs require primary-source verification before production changes.

Page Role Guidance

news_brief: concise visible summary, source link, paired longform link when available. Do not force TLDR if the brief already is the short form.
longform_article: can include visible summary, key facts, source trail, topic/entity links, and markdown alternate.
topic: good candidate for direct answer and entity/topic explanation.
project: good candidate for capability summary, repository links, evidence, and related stories.
author: good candidate for Person/entity context and trust signals.
home: can include a concise site purpose and section map.

Safety And Privacy Boundaries

Do not include admin, API, private dashboards, raw analytics, raw IP logs, secrets, unpublished drafts, staging URLs, or internal planning notes in llms.txt, markdown alternates, source trails, or entity maps.
Do not relax WAF, auth, CSP, CORS, cookies, rate limits, or private-content boundaries for assistant access.
Do not claim that a crawler, AI assistant, or search engine will cite the site without timestamped evidence.

Validation

Before marking work complete:

every LLM-facing URL is public, canonical, useful, and non-private;
every answer/source block is visible to humans;
every markdown alternate has a corresponding canonical HTML page;
no duplicate public story body is introduced;
crawler policy items are marked as verified or requiring verification;
citation/monitoring claims are handed off to a monitoring task.

Validate skill edits with:

python3 <codex-skills-dir>/senior-skill-architect/scripts/lint_production_skill.py ./skills/llm-friendly-site-architect
python3 ./plans/seo-llm-skill-cluster/scripts/lint_skill_cluster.py .

Forward tests live in evals.json.

Output Shape

Return:

LLM-readable architecture summary.
llms.txt section plan.
Visible answer/source/entity block plan.
Markdown alternate policy.
Crawler verification needs.
Refused or deferred items.

Voir la source ↗

Métadonnées du fichier

name: llm-friendly-site-architect
description: Design human-visible, machine-readable website layers for AI assistants, RAG, and agentic search. Use this skill when the user asks for llms.txt, LLM discovery plans, visible TLDR or direct-answer blocks, source trails, entity pages, markdown alternates, AI crawler policy, topic-to-URL maps, assistant-readable public content, or LLM-friendly architecture that must preserve canonical SEO strategy without hidden bot-only facts or duplicate story bodies.

Voir le texte original

---
name: llm-friendly-site-architect
description: Design human-visible, machine-readable website layers for AI assistants, RAG, and agentic search. Use this skill when the user asks for llms.txt, LLM discovery plans, visible TLDR or direct-answer blocks, source trails, entity pages, markdown alternates, AI crawler policy, topic-to-URL maps, assistant-readable public content, or LLM-friendly architecture that must preserve canonical SEO strategy without hidden bot-only facts or duplicate story bodies.
---

# LLM Friendly Site Architect

Use this skill after semantic core, URL architecture, internal link graph, and technical SEO/schema foundations exist.

Read [references/llm-readable-architecture.md](references/llm-readable-architecture.md) before producing a full LLM discovery plan.

## Owns

- `llms.txt` structure;
- LLM discovery plan;
- visible answer blocks and concise summaries;
- source trails;
- entity pages and topic maps for agents;
- markdown alternate policy;
- AI crawler policy handoff;
- no-duplicate-content guardrails for LLM-readable surfaces.

## Does Not Own

- Search Console or assistant citation monitoring execution;
- technical schema implementation;
- URL/canonical decisions;
- hidden content;
- external authority placement.

## Workflow

1. Read `url-map.yaml`, `internal-link-graph.yaml`, schema/head policy, and visible content model.
2. Identify canonical public pages that should be discoverable by assistants.
3. Draft or audit `llms.txt` sections with only public useful URLs.
4. Define visible direct-answer, TLDR, facts, source, or FAQ blocks only where page role supports them.
5. Define source-trail and citation-ready evidence surfaces.
6. Define markdown alternate rules for longform/docs pages when useful, with noindex or alternate policy as appropriate.
7. Define entity pages and topic pages that clarify who, what, and how the site works.
8. Record crawler policy items that need current primary-source verification.
9. Produce an LLM discovery report using [assets/llm-discovery-report.template.md](assets/llm-discovery-report.template.md).

## Non-Negotiables

- Human-visible content first.
- No hidden bot-only facts.
- No doorway pages.
- No FAQPage schema unless FAQ is visible.
- No automatic TLDR on every short news page by default.
- No extra public story bodies beyond the declared content model.
- `llms.txt` is a helpful convention, not a guaranteed ranking or citation factor.
- Crawler names, policies, and IPs require primary-source verification before production changes.

## Page Role Guidance

- `news_brief`: concise visible summary, source link, paired longform link when available. Do not force TLDR if the brief already is the short form.
- `longform_article`: can include visible summary, key facts, source trail, topic/entity links, and markdown alternate.
- `topic`: good candidate for direct answer and entity/topic explanation.
- `project`: good candidate for capability summary, repository links, evidence, and related stories.
- `author`: good candidate for Person/entity context and trust signals.
- `home`: can include a concise site purpose and section map.

## Safety And Privacy Boundaries

- Do not include admin, API, private dashboards, raw analytics, raw IP logs, secrets, unpublished drafts, staging URLs, or internal planning notes in `llms.txt`, markdown alternates, source trails, or entity maps.
- Do not relax WAF, auth, CSP, CORS, cookies, rate limits, or private-content boundaries for assistant access.
- Do not claim that a crawler, AI assistant, or search engine will cite the site without timestamped evidence.

## Validation

Before marking work complete:

- every LLM-facing URL is public, canonical, useful, and non-private;
- every answer/source block is visible to humans;
- every markdown alternate has a corresponding canonical HTML page;
- no duplicate public story body is introduced;
- crawler policy items are marked as verified or requiring verification;
- citation/monitoring claims are handed off to a monitoring task.

Validate skill edits with:

```bash
python3 <codex-skills-dir>/senior-skill-architect/scripts/lint_production_skill.py ./skills/llm-friendly-site-architect
python3 ./plans/seo-llm-skill-cluster/scripts/lint_skill_cluster.py .
```

Forward tests live in [evals.json](evals.json).

## Output Shape

Return:

1. LLM-readable architecture summary.
2. `llms.txt` section plan.
3. Visible answer/source/entity block plan.
4. Markdown alternate policy.
5. Crawler verification needs.
6. Refused or deferred items.

Examiner la source

Prix et coûts d’utilisation

Obtenir le skill: Prix non confirmé
L’utiliser: Prérequis non confirmés. Consultez les frais d’agent, d’API et de services à la source.
Licence: MIT
Prix non confirmé: Le prix n’est pas confirmé. Les liens existants vers les sources et l’installation restent disponibles.

Gratuit à obtenir ne signifie pas gratuit à utiliser. Le prix ne constitue pas une évaluation de sécurité. Soumettre un prix →

Source du skill enregistrée

Un chemin vers les instructions est enregistré. Cela ne constitue pas un test, une garantie de sécurité ou de compatibilité.

Réviser avant installation: Éviter l’installation automatique

Licence: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
L’approbation de revue IA est absente
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 39 GitHub stars
Stars/forks activity: 39 stars, 3 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Ouvrir l’audit complet

Les outils sont des indications de métadonnées, pas une compatibilité testée. Les prompts sont des suggestions.

Commencer par une petite tâche

1Lisez la source et confirmez entrées, résultats, dépendances et permissions.
2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.

Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.

Source et conseils d’utilisation

RépertoriéContrôle statique

Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.

Dépôt source: sergekostenchuk/seo-llm-skill-cluster
Licence: MIT
Version: Unknown
Dernier push GitHub: 11 juin 2026
Registre mis à jour: 10 sept. 2026
Chemin des instructions: skills/llm-friendly-site-architect/SKILL.md @ 5873665900e0

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

47/100

Revue nécessaire

Confiance

56/100

Do not auto-install

Audit

65/100

Revue nécessaire

Ouvrir l’audit complet Voir le rapport d’évaluation

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
L’approbation de revue IA est absente
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 39 GitHub stars
Stars/forks activity: 39 stars, 3 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Verified installs: —
Résultats: —

Copier ne signifie pas installer. Les compteurs nécessitent un rapport de réussite et ne garantissent pas la qualité globale.

Accès agent

L’API Registry fournit les signaux de décision, confiance, audit, cas d’usage et installation sans analyser l’interface.

Ouvrir l’API d’installation Format texte LLM Ouvrir Manifest Plan de résolution auto

Plus de détails

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    "description": "Design human-visible, machine-readable website layers for AI assistants, RAG, and agentic search. Use this skill when the user asks for llms.txt, LLM discovery plans, visible TLDR or direct-answer blocks, source trails, entity pages, markdown alternates, AI crawler policy, topic-to-URL maps, assistant-readable public content, or LLM-friendly architecture that must preserve canonical SEO strategy without hidden bot-only facts or duplicate story bodies.",
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      "documentation": "Usable metadata, review docs",
      "agentOutcomes": "No agent outcome data yet"
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      "label": "No agent outcome data yet"
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      "GitHub adoption: 39 GitHub stars",
      "Stars/forks activity: 39 stars, 3 forks; issue activity unavailable in current metadata",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
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    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
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    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
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  "quality": {
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    "label": "Needs review"
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  "supply": {
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    "scenario": "Research agents",
    "maintenance": "4mo since push",
    "risk": "Needs review"
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  "alternative_skills": [
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      "stars": 13443,
      "install_command": "npx skills add Orchestra-Research/AI-Research-SKILLs --skill peft-fine-tuning",
      "trust_score": 80,
      "audit_score": 85
    }
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    "production agents without a repository review",
    "Low GitHub adoption signal",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "AI review approval is missing",
    "Quality score needs review"
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  "agent_contract": {
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    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 64/100 Manual review",
      "Audit: 65/100 Needs review",
      "Safety: 17/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
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      "install_command": "npx skills add sergekostenchuk/seo-llm-skill-cluster --skill llm-friendly-site-architect",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
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    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "sergekostenchuk-llm-friendly-site-architect",
      "task": "Use llm-friendly-site-architect in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/sergekostenchuk-llm-friendly-site-architect",
    "api": "https://www.openagentskill.com/api/agent/skills/sergekostenchuk-llm-friendly-site-architect",
    "audit": "https://www.openagentskill.com/skills/sergekostenchuk-llm-friendly-site-architect/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=sergekostenchuk-llm-friendly-site-architect&task=Use%20llm-friendly-site-architect%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20llm-friendly-site-architect%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20llm-friendly-site-architect%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/sergekostenchuk-llm-friendly-site-architect/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/sergekostenchuk-llm-friendly-site-architect"
  }
}

Pour le créateur

Source de la fiche

Indexé par Registry

Revendiable

Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.

Créateur: sergekostenchuk
Source: sergekostenchuk/seo-llm-skill-cluster
Indexé par: Index communautaire OpenAgentSkill

L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.

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