Agent skill

artifact-analysis

Use when the user wants a cited, structured read of local documents and project knowledge. Triggers on: \"analyze these docs\", \"scan my project for context\", \"read the docs folder\", \"summarize what's in .beagle/concepts/\", \"extract context from docs/\", \"what's in this folder\", \"go read everything in X and tell me what's there\". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups (\"find this function\", \"search the rep

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill artifact-analysis --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 17 KB
Bundled scripts: none
Path: skills/analysis/artifact-analysis/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Artifact Analysis Turn a set of local paths (or a beagle project's conventional knowledge locations) into a cited, structured extraction of insights, context, decisions, and raw detail. The deliverable is always on disk: a written scan plan the caller can audit, one findings file per slice, and a synthesized report with path-anchored citations. Nothing returns as inline prose, and no claim ships without a source path + verbatim excerpt behind it. ## When to use - A user asks for a local-document read — "analyze the docs folder", "scan the project for context", "extract what's in .beagle/concepts/". - Another beagle skill invokes this one programmatically as a grounding companion (see `references/companion-contract.md`). - The caller wants auditable output: a plan written before extraction, findings files per slice, and a citation-backed synthesis report. ## When NOT to use - Codebase lookups ("where is this function defined", "grep for this symbol"). Use Grep/Glob. - Web research. Use `web-research`. - Comparative evaluation of two implementations or source credibility adjudication. Use `llm-judge`. - Rewriting or editing the scanned documents. Use `humanize-beagle` or the file t

What's inside
Steps it walks through
  1. When to use
  2. When NOT to use
  3. Workflow
  4. Hard gates
  5. Inputs
  6. Auto-discovery
  7. Intent modes
  8. Output location
  9. The scan plan (plan.md)
  10. Subagent dispatch
  11. Skim strategies
  12. Skip patterns
  13. Citations
  14. Synthesis (report.md)
Ships with 1 file
  • metadata.json
More from claude-skill-registry
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About this skill
What does the artifact-analysis skill do?

Use when the user wants a cited, structured read of local documents and project knowledge. Triggers on: \"analyze these docs\", \"scan my project for context\", \"read the docs folder\", \"summarize what's in .beagle/concepts/\", \"extract context from docs/\", \"what's in this folder\", \"go read everything in X and tell me what's there\". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups (\"find this function\", \"search the rep

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill artifact-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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