agentleFS
bryanwhlbryanwhl/skill-graph/agent-skill/SKILL.md

skill-graph

Skill2 starsChanged 6 months agoMITView on GitHub

Use the local skill-graph CLI to resolve tasks into graph-based skill context, load shallow context first, and expand full skills only when needed.

1 other project uses a version of this.

Adopted by

Most recently taken up by

  • Other versions1 project uses a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 1

    1. Vix0007/vixero-skills★ 1same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository5 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

12 rules. About 0 are common, 11 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈11

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when a task could benefit from specialized agent skills, especially work involving frontend polish, testing, documentation, …

    line 8
  2. Distinctive:

    Ask before installing any remote skill.

    line 32
  3. Distinctive:

    Prefer installed local skills when they are good enough.

    line 53
  4. Distinctive:

    Use ancestors at shallow depth.

    line 54
  5. Distinctive:

    Use direct matches at the deepest useful depth allowed by budget.

    line 55
  6. Distinctive:

    Keep complements on the frontier until the task requires them.

    line 56
  7. Distinctive:

    Treat conflicts as warnings that need human review before loading both skills at full depth.

    line 57
  8. Distinctive:

    Treat inferred edge suggestions as review items, not active resolver policy.

    line 58
  9. Distinctive:

    Never install remote skills without explicit user approval.

    line 59
  10. Distinctive:

    Treat remote-cache results as metadata only until the user approves an install.

    line 60
  11. Distinctive:

    Do not enable any embedding provider that uploads local task, repository, or private skill text without explicit human approval.

    line 61
  12. Very specific:

    Do not pass --trust-remote-code unless the user explicitly accepts local execution of model repository code.

    line 62

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

skill-graph

Use this skill when a task could benefit from specialized agent skills, especially work involving frontend polish, testing, documentation, deployment, security review, performance, or framework-specific implementation.

Runtime Loop

  1. Resolve the task before specialized work:

    skill-graph resolve "<task>" --format markdown
  2. Load the selected shallow context first.
  3. Inspect the task and repository.
  4. Expand only nodes justified by new evidence:

    skill-graph expand <node-id> --depth summary
  5. Expand to full context only when the summary is insufficient:

    skill-graph expand <node-id> --depth full
  6. Ask before installing any remote skill.
  7. At the end, report which nodes were loaded and which frontier nodes were skipped.

Commands

  • skill-graph index: scan local skill roots and write .skill-graph/index.json.
  • skill-graph index --skills-sh-query "<query>": include not-installed skills.sh candidates in the graph for the current domain.
  • skill-graph remote-cache "<query>": cache skills.sh candidates and show approval-required install commands.
  • skill-graph embeddings index: build a local semantic embedding index. Use the default qwen3-local provider only when local Python dependencies and model storage are acceptable; use --provider deterministic for tests and demos.
  • skill-graph embeddings index --trust-remote-code: allow model repository code execution only after explicit human review of the model source.
  • skill-graph embeddings info: show the saved local embedding provider, model, dimensions, and vector count.
  • skill-graph edges suggest: propose inferred edges from embedding similarity for human review; do not treat proposed edges as canonical.
  • skill-graph search "<query>": search the local graph with BM25 by default; use --strategy lexical for baseline comparison, --strategy semantic after embeddings exist, or --strategy hybrid for BM25 plus lexical plus semantic fusion.
  • skill-graph resolve "<task>": return selected nodes, context depths, frontier nodes, conflicts, missing nodes, scoring provider provenance, and reasons. Hybrid resolution includes semantic results only when a local embedding index already exists.
  • skill-graph expand <node-id> --depth <depth>: load deeper context for one node.
  • skill-graph context: show context layers loaded in the current workspace.
  • skill-graph explain --last: explain the last resolution path.
  • skill-graph install <node-id>: show the exact dry-run install command for a remote node when available.

Operating Rules

  • Prefer installed local skills when they are good enough.
  • Use ancestors at shallow depth.
  • Use direct matches at the deepest useful depth allowed by budget.
  • Keep complements on the frontier until the task requires them.
  • Treat conflicts as warnings that need human review before loading both skills at full depth.
  • Treat inferred edge suggestions as review items, not active resolver policy.
  • Never install remote skills without explicit user approval.
  • Treat remote-cache results as metadata only until the user approves an install.
  • Do not enable any embedding provider that uploads local task, repository, or private skill text without explicit human approval.
  • Do not pass --trust-remote-code unless the user explicitly accepts local execution of model repository code.

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