Creator · VZezelin
Last updated · Sep 5, 2026
Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent nee
Creator · VZezelin
Last updated · Sep 5, 2026
Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent nee
Creator · VZezelin
Last updated · Sep 5, 2026
Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent nee
Creator · VZezelin
Last updated · Sep 5, 2026
Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent nee
Do not auto-install
Install targets
Codex install prompt
Install the "signal-lab-apify-tools" agent skill from https://github.com/VZezelin/first/tree/main/skills/signal-lab-apify-tools. 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: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent needs one of these public-data workflows and should choose a bounded, truthful Apify or MCP path instead of inventing scraping capabilities. 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":"vzezelin-first-signal-lab-apify-tools","task":"Install signal-lab-apify-tools","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 VZezelin/first --skill signal-lab-apify-tools
Maintenance
fresh
Pushed today
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
0
57/100 Quality · 65/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · The SKILL.md is truncated in the excerpt, but the provided content appears complete enough for evaluation.
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
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
0 GitHub stars
Repo activity
0 stars, 0 forks
Maintenance
Pushed today
License
MIT
Install
npx skills add VZezelin/first --skill signal-lab-apify-tools
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 VZezelin/first --skill signal-lab-apify-toolsDo not use when
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.
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.
high
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
medium
Skill may inspect schemas, query databases, or work with persistent stores.
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%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/vzezelin-first-signal-lab-apify-tools/install
Agent should check
Copy prompt
Task: Use signal-lab-apify-tools in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/vzezelin-first-signal-lab-apify-tools/install
Install command: npx skills add VZezelin/first --skill signal-lab-apify-tools
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/vzezelin-first-signal-lab-apify-tools/install
LLM text format
/api/skills/vzezelin-first-signal-lab-apify-tools/install?format=text
Find alternatives
/api/skills/search?q=signal-lab-apify-tools&limit=3
Agent prompt
Use signal-lab-apify-tools for this task. Review https://www.openagentskill.com/api/skills/vzezelin-first-signal-lab-apify-tools/install, then install with: npx skills add VZezelin/first --skill signal-lab-apify-toolsRegistry 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/vzezelin-first-signal-lab-apify-tools
LLM text
/api/registry/manifest/vzezelin-first-signal-lab-apify-tools?format=text
Install alias
/api/registry/install/vzezelin-first-signal-lab-apify-tools
Recommend
/api/registry/recommend?task=Use%20signal-lab-apify-tools%20in%20an%20agent%20workflow&limit=3
Agent fit
Web scraping
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Do a manual repository review before adding this to an agent workflow.
Role in stack
Needs validation
Primary fit
Web scraping
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub adoption
FIX0 GitHub stars
Stars/forks activity
FIX0 stars, 0 forks; issue activity unavailable in current metadata
Recent maintenance
PASSPushed today
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Choose a stronger alternative or inspect the source manually before any install attempt.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Collect structured data
I need my agent to scrape websites and extract structured data from pages.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
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.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
--- name: signal-lab-apify-tools description: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent needs one of these public-data workflows and should choose a bounded, truthful Apify or MCP path instead of inventing scraping capabilities. license: MIT compatibility: Requires network access and the user's own Apify authentication for paid Actor or MCP execution. Never use or request Signal Lab owner credentials. metadata: author: Signal Lab homepage: https://first-livid-omega.vercel.app/ registry: io.github.VZezelin/signal-lab-apify-tools ---
# Signal Lab Apify Tools
Use Signal Lab as a routing skill for a small set of focused public-data workflows. Prefer the narrowest Actor that matches the task, keep inputs bounded, and treat the live Apify Actor input schema and Pricing tab as the source of truth.
## Use When
- The user needs available public YouTube captions or timestamped caption segments for research, RAG, or analysis. - The user needs a public website or bounded same-domain crawl converted to clean Markdown for RAG, semantic search, indexing, or LLM analysis. - The user already has one or more public job-posting URLs and needs normalized job fields, especially Schema.org `JobPosting` data when exposed by the page. - The user needs public Amazon product price or availability tracking, live Google Autocomplete keyword suggestions, public Reddit research, or supported restaurant-menu extraction. - An MCP-capable client should expose one or more Signal Lab Actors as tools through Apify's hosted MCP server. - A non-MCP workflow should call the corresponding Actor through the Apify REST API and consume its Dataset.
## Don't Use When
- The task requires bypassing login walls, paywalls, CAPTCHAs, robots restrictions, anti-bot controls, private pages, or other access controls. - The user asks for audio transcription of a YouTube video with no accessible public caption track; the YouTube Actor extracts available captions and is not a speech-to-text service. - The website requires client-side JavaScript rendering that an HTTP-only crawler cannot provide; do not claim the Website to Markdown Actor renders SPAs. - The user wants broad job-board discovery rather than extraction from known supported public job URLs; do not imply the Job Vacancy Scraper searches every job board. - The requested source or use would violate applicable law, privacy requirements, copyright obligations, site terms, or the user's authorization. - The task can be answered directly without external data execution; do not start an Actor just to demonstrate the skill.
## Workflow
1. Identify the exact data need and select the narrowest matching tool. - YouTube captions: `signal_lab/youtube-transcript-scraper` - Website to Markdown: `signal_lab/website-to-markdown-crawler` - Known public job URL extraction: `signal_lab/job-vacancy-scraper` - Amazon price tracking: `signal_lab/amazon-price-tracker` - Google Autocomplete research: `signal_lab/google-autocomplete-keywords` - Reddit public research: `signal_lab/reddit-search-comments` - Restaurant menu extraction: `signal_lab/restaurant-menu-extractor` 2. Read the tool's live Apify input schema and Pricing tab before execution. Pricing, availability, and schema can change; documentation examples are not a substitute for live state. 3. Choose the execution surface. - Prefer Apify hosted MCP when the client supports MCP and the user can authenticate with Apify. - Otherwise use the Apify REST Actor API with the user's own Apify token. 4. Start with the smallest useful bounded input. - For crawls, minimize page count and depth first. - For lists of URLs/videos/products, test a small subset before expanding. - Never increase spend or scope merely to collect more data. 5. Wait for the run to finish, then consume the default Dataset or the Actor's documented output. 6. Verify that returned fields actually came from the source. Missing source fields are not evidence that they exist. 7. Scale only after the first bounded result is useful and the user accepts the live pricing/economics.
## Rules
- Always use the user's own Apify authentication for paid execution or MCP authorization. - Never embed, expose, proxy, or request Signal Lab owner credentials. - Never treat a public Actor run counter, total users, a directory listing, or a successful API request as proof of creator revenue. - Never promise fields the source page or caption track does not expose. - Never claim access-control bypass capabilities. - Prefer reversible, bounded calls and the minimum required data volume. - Use the live Apify Pricing tab as the commercial source of truth before execution. - For Website to Markdown, respect its HTTP-crawler limitation and bounded crawl controls. - For YouTube, describe output as available public captions/timestamps, not newly generated transcription. - For Job Posting extraction, describe it as known-public-URL extraction and Schema.org-aware parsing, not universal job search.
## Examples
### YouTube captions for RAG
User need: "Get timestamps from these public YouTube videos so I can build a citation-aware RAG index."
Use `signal_lab/youtube-transcript-scraper` with a small set of public URLs, request timestamped segments, then preserve source URL, language, transcript text, and segment timing when building the downstream index.
### Website documentation to Markdown
User need: "Turn this documentation site into a small Markdown corpus for my LLM."
Use `signal_lab/website-to-markdown-crawler`. Start with one page or a low `maxPages` value, keep `sameDomainOnly` enabled, keep crawl depth low, and respect robots rules. Inspect the first Dataset rows before expanding.
### Known job posting to structured JSON
User need: "Normalize title, company, location, salary, and dates from these five job URLs."
Use `signal_lab/job-vacancy-scraper` only for the supplied public URLs. Return fields that the pages actually expose and note missing values rather than fabricating them.
### MCP connection
For a focused Website to Markdown tool, an MCP-capable client can use:
```json { "mcpServers": { "signal-lab-markdown": { "url": "https://mcp.apify.com?tools=signal_lab/website-to-markdown-crawler" } } } ```
Apify handles authentication. Do not put an owner token into shared configuration.
## Edge Cases
- If Apify authentication is unavailable, provide the correct Actor or MCP connection path but do not execute paid work on somebody else's credentials. - If the live Actor schema differs from this skill, follow the live schema and update assumptions accordingly. - If the page is JavaScript-only and the HTTP crawler returns incomplete content, stop and explain the rendering limitation instead of escalating into access-control bypass techniques. - If YouTube exposes no usable public captions, stop and report that limitation; do not silently switch to a different paid transcription product. - If a job page lacks salary or structured metadata, return the fields that are verifiably present and mark the rest missing. - If a requested run could become large or costly, shrink the initial input and ask for approval before materially expanding spend.
## References
- Signal Lab developer hub: https://first-livid-omega.vercel.app/ - AI-agent discovery index: https://first-livid-omega.vercel.app/llms.txt - Official MCP Registry identity: `io.github.VZezelin/signal-lab-apify-tools` - Official MCP Registry search: https://registry.modelcontextprotocol.io/?q=io.github.VZezelin%2Fsignal-lab-apify-tools - Signal Lab on Apify: https://apify.com/signal_lab - YouTube Transcript API guide: https://first-livid-omega.vercel.app/youtube-transcript-api.html - Website to Markdown API guide: https://first-livid-omega.vercel.app/website-to-markdown-api.html - Job Posting Scraper API guide: https://first-livid-omega.vercel.app/job-posting-scraper-api.html
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 signal-lab-apify-tools, ready for a manual X post.
signal-lab-apify-tools: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, w... 0 stars https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=x
Listing + install path for signal-lab-apify-tools: https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=x Install: npx skills add VZezelin/first --skill signal-lab-apify-tools
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 Community submitted listing is attributed to VZezelin 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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Do not auto-install
Do not auto-install
Install targets
Codex install prompt
Install the "signal-lab-apify-tools" agent skill from https://github.com/VZezelin/first/tree/main/skills/signal-lab-apify-tools. 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: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent needs one of these public-data workflows and should choose a bounded, truthful Apify or MCP path instead of inventing scraping capabilities. 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":"vzezelin-first-signal-lab-apify-tools","task":"Install signal-lab-apify-tools","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 VZezelin/first --skill signal-lab-apify-tools
Maintenance
fresh
Pushed today
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
0
57/100 Quality · 65/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · The SKILL.md is truncated in the excerpt, but the provided content appears complete enough for evaluation.
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
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
0 GitHub stars
Repo activity
0 stars, 0 forks
Maintenance
Pushed today
License
MIT
Install
npx skills add VZezelin/first --skill signal-lab-apify-tools
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 VZezelin/first --skill signal-lab-apify-toolsDo not use when
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.
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.
high
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
medium
Skill may inspect schemas, query databases, or work with persistent stores.
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%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/vzezelin-first-signal-lab-apify-tools/install
Agent should check
Copy prompt
Task: Use signal-lab-apify-tools in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/vzezelin-first-signal-lab-apify-tools/install
Install command: npx skills add VZezelin/first --skill signal-lab-apify-tools
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/vzezelin-first-signal-lab-apify-tools/install
LLM text format
/api/skills/vzezelin-first-signal-lab-apify-tools/install?format=text
Find alternatives
/api/skills/search?q=signal-lab-apify-tools&limit=3
Agent prompt
Use signal-lab-apify-tools for this task. Review https://www.openagentskill.com/api/skills/vzezelin-first-signal-lab-apify-tools/install, then install with: npx skills add VZezelin/first --skill signal-lab-apify-toolsRegistry 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/vzezelin-first-signal-lab-apify-tools
LLM text
/api/registry/manifest/vzezelin-first-signal-lab-apify-tools?format=text
Install alias
/api/registry/install/vzezelin-first-signal-lab-apify-tools
Recommend
/api/registry/recommend?task=Use%20signal-lab-apify-tools%20in%20an%20agent%20workflow&limit=3
Agent fit
Web scraping
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Do a manual repository review before adding this to an agent workflow.
Role in stack
Needs validation
Primary fit
Web scraping
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub adoption
FIX0 GitHub stars
Stars/forks activity
FIX0 stars, 0 forks; issue activity unavailable in current metadata
Recent maintenance
PASSPushed today
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Choose a stronger alternative or inspect the source manually before any install attempt.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Collect structured data
I need my agent to scrape websites and extract structured data from pages.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
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.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
--- name: signal-lab-apify-tools description: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent needs one of these public-data workflows and should choose a bounded, truthful Apify or MCP path instead of inventing scraping capabilities. license: MIT compatibility: Requires network access and the user's own Apify authentication for paid Actor or MCP execution. Never use or request Signal Lab owner credentials. metadata: author: Signal Lab homepage: https://first-livid-omega.vercel.app/ registry: io.github.VZezelin/signal-lab-apify-tools ---
# Signal Lab Apify Tools
Use Signal Lab as a routing skill for a small set of focused public-data workflows. Prefer the narrowest Actor that matches the task, keep inputs bounded, and treat the live Apify Actor input schema and Pricing tab as the source of truth.
## Use When
- The user needs available public YouTube captions or timestamped caption segments for research, RAG, or analysis. - The user needs a public website or bounded same-domain crawl converted to clean Markdown for RAG, semantic search, indexing, or LLM analysis. - The user already has one or more public job-posting URLs and needs normalized job fields, especially Schema.org `JobPosting` data when exposed by the page. - The user needs public Amazon product price or availability tracking, live Google Autocomplete keyword suggestions, public Reddit research, or supported restaurant-menu extraction. - An MCP-capable client should expose one or more Signal Lab Actors as tools through Apify's hosted MCP server. - A non-MCP workflow should call the corresponding Actor through the Apify REST API and consume its Dataset.
## Don't Use When
- The task requires bypassing login walls, paywalls, CAPTCHAs, robots restrictions, anti-bot controls, private pages, or other access controls. - The user asks for audio transcription of a YouTube video with no accessible public caption track; the YouTube Actor extracts available captions and is not a speech-to-text service. - The website requires client-side JavaScript rendering that an HTTP-only crawler cannot provide; do not claim the Website to Markdown Actor renders SPAs. - The user wants broad job-board discovery rather than extraction from known supported public job URLs; do not imply the Job Vacancy Scraper searches every job board. - The requested source or use would violate applicable law, privacy requirements, copyright obligations, site terms, or the user's authorization. - The task can be answered directly without external data execution; do not start an Actor just to demonstrate the skill.
## Workflow
1. Identify the exact data need and select the narrowest matching tool. - YouTube captions: `signal_lab/youtube-transcript-scraper` - Website to Markdown: `signal_lab/website-to-markdown-crawler` - Known public job URL extraction: `signal_lab/job-vacancy-scraper` - Amazon price tracking: `signal_lab/amazon-price-tracker` - Google Autocomplete research: `signal_lab/google-autocomplete-keywords` - Reddit public research: `signal_lab/reddit-search-comments` - Restaurant menu extraction: `signal_lab/restaurant-menu-extractor` 2. Read the tool's live Apify input schema and Pricing tab before execution. Pricing, availability, and schema can change; documentation examples are not a substitute for live state. 3. Choose the execution surface. - Prefer Apify hosted MCP when the client supports MCP and the user can authenticate with Apify. - Otherwise use the Apify REST Actor API with the user's own Apify token. 4. Start with the smallest useful bounded input. - For crawls, minimize page count and depth first. - For lists of URLs/videos/products, test a small subset before expanding. - Never increase spend or scope merely to collect more data. 5. Wait for the run to finish, then consume the default Dataset or the Actor's documented output. 6. Verify that returned fields actually came from the source. Missing source fields are not evidence that they exist. 7. Scale only after the first bounded result is useful and the user accepts the live pricing/economics.
## Rules
- Always use the user's own Apify authentication for paid execution or MCP authorization. - Never embed, expose, proxy, or request Signal Lab owner credentials. - Never treat a public Actor run counter, total users, a directory listing, or a successful API request as proof of creator revenue. - Never promise fields the source page or caption track does not expose. - Never claim access-control bypass capabilities. - Prefer reversible, bounded calls and the minimum required data volume. - Use the live Apify Pricing tab as the commercial source of truth before execution. - For Website to Markdown, respect its HTTP-crawler limitation and bounded crawl controls. - For YouTube, describe output as available public captions/timestamps, not newly generated transcription. - For Job Posting extraction, describe it as known-public-URL extraction and Schema.org-aware parsing, not universal job search.
## Examples
### YouTube captions for RAG
User need: "Get timestamps from these public YouTube videos so I can build a citation-aware RAG index."
Use `signal_lab/youtube-transcript-scraper` with a small set of public URLs, request timestamped segments, then preserve source URL, language, transcript text, and segment timing when building the downstream index.
### Website documentation to Markdown
User need: "Turn this documentation site into a small Markdown corpus for my LLM."
Use `signal_lab/website-to-markdown-crawler`. Start with one page or a low `maxPages` value, keep `sameDomainOnly` enabled, keep crawl depth low, and respect robots rules. Inspect the first Dataset rows before expanding.
### Known job posting to structured JSON
User need: "Normalize title, company, location, salary, and dates from these five job URLs."
Use `signal_lab/job-vacancy-scraper` only for the supplied public URLs. Return fields that the pages actually expose and note missing values rather than fabricating them.
### MCP connection
For a focused Website to Markdown tool, an MCP-capable client can use:
```json { "mcpServers": { "signal-lab-markdown": { "url": "https://mcp.apify.com?tools=signal_lab/website-to-markdown-crawler" } } } ```
Apify handles authentication. Do not put an owner token into shared configuration.
## Edge Cases
- If Apify authentication is unavailable, provide the correct Actor or MCP connection path but do not execute paid work on somebody else's credentials. - If the live Actor schema differs from this skill, follow the live schema and update assumptions accordingly. - If the page is JavaScript-only and the HTTP crawler returns incomplete content, stop and explain the rendering limitation instead of escalating into access-control bypass techniques. - If YouTube exposes no usable public captions, stop and report that limitation; do not silently switch to a different paid transcription product. - If a job page lacks salary or structured metadata, return the fields that are verifiably present and mark the rest missing. - If a requested run could become large or costly, shrink the initial input and ask for approval before materially expanding spend.
## References
- Signal Lab developer hub: https://first-livid-omega.vercel.app/ - AI-agent discovery index: https://first-livid-omega.vercel.app/llms.txt - Official MCP Registry identity: `io.github.VZezelin/signal-lab-apify-tools` - Official MCP Registry search: https://registry.modelcontextprotocol.io/?q=io.github.VZezelin%2Fsignal-lab-apify-tools - Signal Lab on Apify: https://apify.com/signal_lab - YouTube Transcript API guide: https://first-livid-omega.vercel.app/youtube-transcript-api.html - Website to Markdown API guide: https://first-livid-omega.vercel.app/website-to-markdown-api.html - Job Posting Scraper API guide: https://first-livid-omega.vercel.app/job-posting-scraper-api.html
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 signal-lab-apify-tools, ready for a manual X post.
signal-lab-apify-tools: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, w... 0 stars https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=x
Listing + install path for signal-lab-apify-tools: https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=x Install: npx skills add VZezelin/first --skill signal-lab-apify-tools
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
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[](https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools/audit)
[](https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)VZezelin
@vzezelin
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Do not auto-install
Do not auto-install
Install targets
Codex install prompt
Install the "signal-lab-apify-tools" agent skill from https://github.com/VZezelin/first/tree/main/skills/signal-lab-apify-tools. 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: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent needs one of these public-data workflows and should choose a bounded, truthful Apify or MCP path instead of inventing scraping capabilities. 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":"vzezelin-first-signal-lab-apify-tools","task":"Install signal-lab-apify-tools","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 VZezelin/first --skill signal-lab-apify-tools
Maintenance
fresh
Pushed today
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
0
57/100 Quality · 65/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · The SKILL.md is truncated in the excerpt, but the provided content appears complete enough for evaluation.
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
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
0 GitHub stars
Repo activity
0 stars, 0 forks
Maintenance
Pushed today
License
MIT
Install
npx skills add VZezelin/first --skill signal-lab-apify-tools
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 VZezelin/first --skill signal-lab-apify-toolsDo not use when
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.
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.
high
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
medium
Skill may inspect schemas, query databases, or work with persistent stores.
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%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/vzezelin-first-signal-lab-apify-tools/install
Agent should check
Copy prompt
Task: Use signal-lab-apify-tools in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/vzezelin-first-signal-lab-apify-tools/install
Install command: npx skills add VZezelin/first --skill signal-lab-apify-tools
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/vzezelin-first-signal-lab-apify-tools/install
LLM text format
/api/skills/vzezelin-first-signal-lab-apify-tools/install?format=text
Find alternatives
/api/skills/search?q=signal-lab-apify-tools&limit=3
Agent prompt
Use signal-lab-apify-tools for this task. Review https://www.openagentskill.com/api/skills/vzezelin-first-signal-lab-apify-tools/install, then install with: npx skills add VZezelin/first --skill signal-lab-apify-toolsRegistry 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/vzezelin-first-signal-lab-apify-tools
LLM text
/api/registry/manifest/vzezelin-first-signal-lab-apify-tools?format=text
Install alias
/api/registry/install/vzezelin-first-signal-lab-apify-tools
Recommend
/api/registry/recommend?task=Use%20signal-lab-apify-tools%20in%20an%20agent%20workflow&limit=3
Agent fit
Web scraping
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Do a manual repository review before adding this to an agent workflow.
Role in stack
Needs validation
Primary fit
Web scraping
Trust label
Needs manual review
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub adoption
FIX0 GitHub stars
Stars/forks activity
FIX0 stars, 0 forks; issue activity unavailable in current metadata
Recent maintenance
PASSPushed today
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Choose a stronger alternative or inspect the source manually before any install attempt.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Collect structured data
I need my agent to scrape websites and extract structured data from pages.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
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.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
--- name: signal-lab-apify-tools description: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent needs one of these public-data workflows and should choose a bounded, truthful Apify or MCP path instead of inventing scraping capabilities. license: MIT compatibility: Requires network access and the user's own Apify authentication for paid Actor or MCP execution. Never use or request Signal Lab owner credentials. metadata: author: Signal Lab homepage: https://first-livid-omega.vercel.app/ registry: io.github.VZezelin/signal-lab-apify-tools ---
# Signal Lab Apify Tools
Use Signal Lab as a routing skill for a small set of focused public-data workflows. Prefer the narrowest Actor that matches the task, keep inputs bounded, and treat the live Apify Actor input schema and Pricing tab as the source of truth.
## Use When
- The user needs available public YouTube captions or timestamped caption segments for research, RAG, or analysis. - The user needs a public website or bounded same-domain crawl converted to clean Markdown for RAG, semantic search, indexing, or LLM analysis. - The user already has one or more public job-posting URLs and needs normalized job fields, especially Schema.org `JobPosting` data when exposed by the page. - The user needs public Amazon product price or availability tracking, live Google Autocomplete keyword suggestions, public Reddit research, or supported restaurant-menu extraction. - An MCP-capable client should expose one or more Signal Lab Actors as tools through Apify's hosted MCP server. - A non-MCP workflow should call the corresponding Actor through the Apify REST API and consume its Dataset.
## Don't Use When
- The task requires bypassing login walls, paywalls, CAPTCHAs, robots restrictions, anti-bot controls, private pages, or other access controls. - The user asks for audio transcription of a YouTube video with no accessible public caption track; the YouTube Actor extracts available captions and is not a speech-to-text service. - The website requires client-side JavaScript rendering that an HTTP-only crawler cannot provide; do not claim the Website to Markdown Actor renders SPAs. - The user wants broad job-board discovery rather than extraction from known supported public job URLs; do not imply the Job Vacancy Scraper searches every job board. - The requested source or use would violate applicable law, privacy requirements, copyright obligations, site terms, or the user's authorization. - The task can be answered directly without external data execution; do not start an Actor just to demonstrate the skill.
## Workflow
1. Identify the exact data need and select the narrowest matching tool. - YouTube captions: `signal_lab/youtube-transcript-scraper` - Website to Markdown: `signal_lab/website-to-markdown-crawler` - Known public job URL extraction: `signal_lab/job-vacancy-scraper` - Amazon price tracking: `signal_lab/amazon-price-tracker` - Google Autocomplete research: `signal_lab/google-autocomplete-keywords` - Reddit public research: `signal_lab/reddit-search-comments` - Restaurant menu extraction: `signal_lab/restaurant-menu-extractor` 2. Read the tool's live Apify input schema and Pricing tab before execution. Pricing, availability, and schema can change; documentation examples are not a substitute for live state. 3. Choose the execution surface. - Prefer Apify hosted MCP when the client supports MCP and the user can authenticate with Apify. - Otherwise use the Apify REST Actor API with the user's own Apify token. 4. Start with the smallest useful bounded input. - For crawls, minimize page count and depth first. - For lists of URLs/videos/products, test a small subset before expanding. - Never increase spend or scope merely to collect more data. 5. Wait for the run to finish, then consume the default Dataset or the Actor's documented output. 6. Verify that returned fields actually came from the source. Missing source fields are not evidence that they exist. 7. Scale only after the first bounded result is useful and the user accepts the live pricing/economics.
## Rules
- Always use the user's own Apify authentication for paid execution or MCP authorization. - Never embed, expose, proxy, or request Signal Lab owner credentials. - Never treat a public Actor run counter, total users, a directory listing, or a successful API request as proof of creator revenue. - Never promise fields the source page or caption track does not expose. - Never claim access-control bypass capabilities. - Prefer reversible, bounded calls and the minimum required data volume. - Use the live Apify Pricing tab as the commercial source of truth before execution. - For Website to Markdown, respect its HTTP-crawler limitation and bounded crawl controls. - For YouTube, describe output as available public captions/timestamps, not newly generated transcription. - For Job Posting extraction, describe it as known-public-URL extraction and Schema.org-aware parsing, not universal job search.
## Examples
### YouTube captions for RAG
User need: "Get timestamps from these public YouTube videos so I can build a citation-aware RAG index."
Use `signal_lab/youtube-transcript-scraper` with a small set of public URLs, request timestamped segments, then preserve source URL, language, transcript text, and segment timing when building the downstream index.
### Website documentation to Markdown
User need: "Turn this documentation site into a small Markdown corpus for my LLM."
Use `signal_lab/website-to-markdown-crawler`. Start with one page or a low `maxPages` value, keep `sameDomainOnly` enabled, keep crawl depth low, and respect robots rules. Inspect the first Dataset rows before expanding.
### Known job posting to structured JSON
User need: "Normalize title, company, location, salary, and dates from these five job URLs."
Use `signal_lab/job-vacancy-scraper` only for the supplied public URLs. Return fields that the pages actually expose and note missing values rather than fabricating them.
### MCP connection
For a focused Website to Markdown tool, an MCP-capable client can use:
```json { "mcpServers": { "signal-lab-markdown": { "url": "https://mcp.apify.com?tools=signal_lab/website-to-markdown-crawler" } } } ```
Apify handles authentication. Do not put an owner token into shared configuration.
## Edge Cases
- If Apify authentication is unavailable, provide the correct Actor or MCP connection path but do not execute paid work on somebody else's credentials. - If the live Actor schema differs from this skill, follow the live schema and update assumptions accordingly. - If the page is JavaScript-only and the HTTP crawler returns incomplete content, stop and explain the rendering limitation instead of escalating into access-control bypass techniques. - If YouTube exposes no usable public captions, stop and report that limitation; do not silently switch to a different paid transcription product. - If a job page lacks salary or structured metadata, return the fields that are verifiably present and mark the rest missing. - If a requested run could become large or costly, shrink the initial input and ask for approval before materially expanding spend.
## References
- Signal Lab developer hub: https://first-livid-omega.vercel.app/ - AI-agent discovery index: https://first-livid-omega.vercel.app/llms.txt - Official MCP Registry identity: `io.github.VZezelin/signal-lab-apify-tools` - Official MCP Registry search: https://registry.modelcontextprotocol.io/?q=io.github.VZezelin%2Fsignal-lab-apify-tools - Signal Lab on Apify: https://apify.com/signal_lab - YouTube Transcript API guide: https://first-livid-omega.vercel.app/youtube-transcript-api.html - Website to Markdown API guide: https://first-livid-omega.vercel.app/website-to-markdown-api.html - Job Posting Scraper API guide: https://first-livid-omega.vercel.app/job-posting-scraper-api.html
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 signal-lab-apify-tools, ready for a manual X post.
signal-lab-apify-tools: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, w... 0 stars https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=x
Listing + install path for signal-lab-apify-tools: https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=x Install: npx skills add VZezelin/first --skill signal-lab-apify-tools
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 Community submitted listing is attributed to VZezelin 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.
[](https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools/audit)
[](https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)VZezelin
@vzezelin
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Do not auto-install
Do not auto-install
Install targets
Codex install prompt
Install the "signal-lab-apify-tools" agent skill from https://github.com/VZezelin/first/tree/main/skills/signal-lab-apify-tools. 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: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent needs one of these public-data workflows and should choose a bounded, truthful Apify or MCP path instead of inventing scraping capabilities. 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":"vzezelin-first-signal-lab-apify-tools","task":"Install signal-lab-apify-tools","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 VZezelin/first --skill signal-lab-apify-tools
Maintenance
fresh
Pushed today
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
0
57/100 Quality · 65/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · The SKILL.md is truncated in the excerpt, but the provided content appears complete enough for evaluation.
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
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
0 GitHub stars
Repo activity
0 stars, 0 forks
Maintenance
Pushed today
License
MIT
Install
npx skills add VZezelin/first --skill signal-lab-apify-tools
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 VZezelin/first --skill signal-lab-apify-toolsDo not use when
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.
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.
high
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
medium
Skill may inspect schemas, query databases, or work with persistent stores.
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%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/vzezelin-first-signal-lab-apify-tools/install
Agent should check
Copy prompt
Task: Use signal-lab-apify-tools in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20signal-lab-apify-tools%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/vzezelin-first-signal-lab-apify-tools/install
Install command: npx skills add VZezelin/first --skill signal-lab-apify-tools
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/vzezelin-first-signal-lab-apify-tools/install
LLM text format
/api/skills/vzezelin-first-signal-lab-apify-tools/install?format=text
Find alternatives
/api/skills/search?q=signal-lab-apify-tools&limit=3
Agent prompt
Use signal-lab-apify-tools for this task. Review https://www.openagentskill.com/api/skills/vzezelin-first-signal-lab-apify-tools/install, then install with: npx skills add VZezelin/first --skill signal-lab-apify-toolsRegistry 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/vzezelin-first-signal-lab-apify-tools
LLM text
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/api/registry/install/vzezelin-first-signal-lab-apify-tools
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/api/registry/recommend?task=Use%20signal-lab-apify-tools%20in%20an%20agent%20workflow&limit=3
Agent fit
Web scraping
Use-case tags
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Claude Code
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Do a manual repository review before adding this to an agent workflow.
Role in stack
Needs validation
Primary fit
Web scraping
Trust label
Needs manual review
Install path
Command ready
Use when
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review first
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Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
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PASSPushed today
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Review before install
Recommended action
Choose a stronger alternative or inspect the source manually before any install attempt.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Collect structured data
I need my agent to scrape websites and extract structured data from pages.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
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.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
--- name: signal-lab-apify-tools description: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, website-to-Markdown RAG ingestion, known job-posting extraction, Amazon price tracking, Google Autocomplete research, Reddit research, and restaurant menu extraction. Use when an agent needs one of these public-data workflows and should choose a bounded, truthful Apify or MCP path instead of inventing scraping capabilities. license: MIT compatibility: Requires network access and the user's own Apify authentication for paid Actor or MCP execution. Never use or request Signal Lab owner credentials. metadata: author: Signal Lab homepage: https://first-livid-omega.vercel.app/ registry: io.github.VZezelin/signal-lab-apify-tools ---
# Signal Lab Apify Tools
Use Signal Lab as a routing skill for a small set of focused public-data workflows. Prefer the narrowest Actor that matches the task, keep inputs bounded, and treat the live Apify Actor input schema and Pricing tab as the source of truth.
## Use When
- The user needs available public YouTube captions or timestamped caption segments for research, RAG, or analysis. - The user needs a public website or bounded same-domain crawl converted to clean Markdown for RAG, semantic search, indexing, or LLM analysis. - The user already has one or more public job-posting URLs and needs normalized job fields, especially Schema.org `JobPosting` data when exposed by the page. - The user needs public Amazon product price or availability tracking, live Google Autocomplete keyword suggestions, public Reddit research, or supported restaurant-menu extraction. - An MCP-capable client should expose one or more Signal Lab Actors as tools through Apify's hosted MCP server. - A non-MCP workflow should call the corresponding Actor through the Apify REST API and consume its Dataset.
## Don't Use When
- The task requires bypassing login walls, paywalls, CAPTCHAs, robots restrictions, anti-bot controls, private pages, or other access controls. - The user asks for audio transcription of a YouTube video with no accessible public caption track; the YouTube Actor extracts available captions and is not a speech-to-text service. - The website requires client-side JavaScript rendering that an HTTP-only crawler cannot provide; do not claim the Website to Markdown Actor renders SPAs. - The user wants broad job-board discovery rather than extraction from known supported public job URLs; do not imply the Job Vacancy Scraper searches every job board. - The requested source or use would violate applicable law, privacy requirements, copyright obligations, site terms, or the user's authorization. - The task can be answered directly without external data execution; do not start an Actor just to demonstrate the skill.
## Workflow
1. Identify the exact data need and select the narrowest matching tool. - YouTube captions: `signal_lab/youtube-transcript-scraper` - Website to Markdown: `signal_lab/website-to-markdown-crawler` - Known public job URL extraction: `signal_lab/job-vacancy-scraper` - Amazon price tracking: `signal_lab/amazon-price-tracker` - Google Autocomplete research: `signal_lab/google-autocomplete-keywords` - Reddit public research: `signal_lab/reddit-search-comments` - Restaurant menu extraction: `signal_lab/restaurant-menu-extractor` 2. Read the tool's live Apify input schema and Pricing tab before execution. Pricing, availability, and schema can change; documentation examples are not a substitute for live state. 3. Choose the execution surface. - Prefer Apify hosted MCP when the client supports MCP and the user can authenticate with Apify. - Otherwise use the Apify REST Actor API with the user's own Apify token. 4. Start with the smallest useful bounded input. - For crawls, minimize page count and depth first. - For lists of URLs/videos/products, test a small subset before expanding. - Never increase spend or scope merely to collect more data. 5. Wait for the run to finish, then consume the default Dataset or the Actor's documented output. 6. Verify that returned fields actually came from the source. Missing source fields are not evidence that they exist. 7. Scale only after the first bounded result is useful and the user accepts the live pricing/economics.
## Rules
- Always use the user's own Apify authentication for paid execution or MCP authorization. - Never embed, expose, proxy, or request Signal Lab owner credentials. - Never treat a public Actor run counter, total users, a directory listing, or a successful API request as proof of creator revenue. - Never promise fields the source page or caption track does not expose. - Never claim access-control bypass capabilities. - Prefer reversible, bounded calls and the minimum required data volume. - Use the live Apify Pricing tab as the commercial source of truth before execution. - For Website to Markdown, respect its HTTP-crawler limitation and bounded crawl controls. - For YouTube, describe output as available public captions/timestamps, not newly generated transcription. - For Job Posting extraction, describe it as known-public-URL extraction and Schema.org-aware parsing, not universal job search.
## Examples
### YouTube captions for RAG
User need: "Get timestamps from these public YouTube videos so I can build a citation-aware RAG index."
Use `signal_lab/youtube-transcript-scraper` with a small set of public URLs, request timestamped segments, then preserve source URL, language, transcript text, and segment timing when building the downstream index.
### Website documentation to Markdown
User need: "Turn this documentation site into a small Markdown corpus for my LLM."
Use `signal_lab/website-to-markdown-crawler`. Start with one page or a low `maxPages` value, keep `sameDomainOnly` enabled, keep crawl depth low, and respect robots rules. Inspect the first Dataset rows before expanding.
### Known job posting to structured JSON
User need: "Normalize title, company, location, salary, and dates from these five job URLs."
Use `signal_lab/job-vacancy-scraper` only for the supplied public URLs. Return fields that the pages actually expose and note missing values rather than fabricating them.
### MCP connection
For a focused Website to Markdown tool, an MCP-capable client can use:
```json { "mcpServers": { "signal-lab-markdown": { "url": "https://mcp.apify.com?tools=signal_lab/website-to-markdown-crawler" } } } ```
Apify handles authentication. Do not put an owner token into shared configuration.
## Edge Cases
- If Apify authentication is unavailable, provide the correct Actor or MCP connection path but do not execute paid work on somebody else's credentials. - If the live Actor schema differs from this skill, follow the live schema and update assumptions accordingly. - If the page is JavaScript-only and the HTTP crawler returns incomplete content, stop and explain the rendering limitation instead of escalating into access-control bypass techniques. - If YouTube exposes no usable public captions, stop and report that limitation; do not silently switch to a different paid transcription product. - If a job page lacks salary or structured metadata, return the fields that are verifiably present and mark the rest missing. - If a requested run could become large or costly, shrink the initial input and ask for approval before materially expanding spend.
## References
- Signal Lab developer hub: https://first-livid-omega.vercel.app/ - AI-agent discovery index: https://first-livid-omega.vercel.app/llms.txt - Official MCP Registry identity: `io.github.VZezelin/signal-lab-apify-tools` - Official MCP Registry search: https://registry.modelcontextprotocol.io/?q=io.github.VZezelin%2Fsignal-lab-apify-tools - Signal Lab on Apify: https://apify.com/signal_lab - YouTube Transcript API guide: https://first-livid-omega.vercel.app/youtube-transcript-api.html - Website to Markdown API guide: https://first-livid-omega.vercel.app/website-to-markdown-api.html - Job Posting Scraper API guide: https://first-livid-omega.vercel.app/job-posting-scraper-api.html
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 signal-lab-apify-tools, ready for a manual X post.
signal-lab-apify-tools: Use Signal Lab's focused Apify data APIs or Official MCP tools for public YouTube captions, w... 0 stars https://www.openagentskill.com/skills/vzezelin-first-signal-lab-apify-tools?ref=x
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Do not auto-install
Permission surface
secrets or environment access, network or browser access
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Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
secrets or environment access, network or browser access
Agent outcomes
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Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
secrets or environment access, network or browser access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
secrets or environment access, network or browser access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness