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SKILL verified MIT Self-run

Skill Graph

skill-bryanwhl-skill-graph-agent-skill · by bryanwhl

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.

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Install

$ agentstack add skill-bryanwhl-skill-graph-agent-skill

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
4mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

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:

``bash skill-graph resolve "" --format markdown ``

  1. Load the selected shallow context first.
  2. Inspect the task and repository.
  3. Expand only nodes justified by new evidence:

``bash skill-graph expand --depth summary ``

  1. Expand to full context only when the summary is insufficient:

``bash skill-graph expand --depth full ``

  1. Ask before installing any remote skill.
  2. 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 "": include not-installed skills.sh candidates in the graph for the current domain.
  • skill-graph remote-cache "": 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 "": 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 "": 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 --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 : 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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.