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Skill alirezarezvani/gaios/.claude/skills/graph

Open-source AI Operating System (AIOS) blueprint for Claude Code & Codex — turn any agent into your personal second brain + Chief of Staff: skills, self-verifying workflows, a second-brain wiki, and deterministic tools. Fork it for any role or domain.

Install
npx -y skills add alirezarezvani/gaios --skill graph

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.

What its author says it does

Copied from the file, not written here

Use when the user wants to build, refresh, or visualize the repo's knowledge graph — code structure plus the committed wiki/ — via graphify. Produces an interactive graph + a GRAPH_REPORT.md of God Nodes, surprising connections, and suggested questions. Trigger on "/graph", "build the knowledge graph", "graph the repo", "map the codebase", "refresh the graph", "visualize the second brain".

SKILL.md

5.4 KB, as published. Nobody here has run it

Knowledge Graph (graphify)

Build a map of how this AIOS actually fits together — which code files and which wiki notes depend on, reference, and cluster with each other — so you can see the structure instead of guessing it. Powered by graphify (a knowledge-graph builder), scoped hard to what's safe to graph.

When to run

  • The user asks to see how the repo / second brain hangs together ("map the codebase", "graph the repo").
  • After meaningful structural change — new skills, tools, SOPs, or a /wiki loop that added entries — to refresh the picture.
  • As a thinking aid before a refactor, an audit, or a /weekly review: what's load-bearing, what's orphaned, what's surprisingly connected.
  • Before exploring with /graph-query (this builds/refreshes the graph it queries).

The output (always this shape)

graphify writes everything to graphify-out/ (git-ignored — a derived artifact, never committed):

## Knowledge graph — <date>
**Built from** — code (local AST) + committed wiki/. Excluded: raw/, .tmp/, .env, secrets.
**Artifacts** — graphify-out/graph.html (interactive) · graph.json · GRAPH_REPORT.md

**God Nodes** — the most-connected hubs (what everything leans on):
1. <node> — <why it's central, in a phrase>
2. … 3. …
**Surprising Connections** — edges you wouldn't expect (cross-domain links worth a look):
- <A> ↔ <B> — <what the link is>
**Suggested Questions** — what the graph invites you to ask next:
- <question> → run `/graph-query "<question>"`

Every edge carries graphify's honesty label — EXTRACTED (read directly), INFERRED (reasoned), or AMBIGUOUS — so claims about the graph cite their basis (cite-don't-invent).

Process

  1. Ensure graphify is installed. Run python tools/graphify_setup.py check. If missing, offer to install (uv tool install graphifyy, fallback pipx install graphifyy / pip install graphifyy, then graphify install --platform claude). No account or signup is needed. Gate: don't proceed until graphify --version resolves.
  2. Set the build scope — code + committed wiki/ ONLY. This is the hard line:
    • Include: source code (Python in tools/, etc.) and the committed wiki/.
    • EXCLUDE always: raw/ (may hold raw PHI/PII/financials before de-identification), .tmp/, .env, graphify-out/, and any sensitive/secret path. Never point graphify's document extraction at raw/.
    • Why this is safe: code is parsed locally by tree-sitter AST (no LLM, nothing leaves the machine); document extraction is limited to wiki/, which is already de-identified and non-confidential per the wiki admission policy. graphify also auto-skips sensitive files during detection — but scope, not that fallback, is your guardrail.
  3. Build the graph.
    • Full build (code + wiki): the heavy document pass runs through graphify's own pipeline using the host IDE session — invoke /graphify . (graphify's global skill), having confirmed scope. Non-code text in wiki/ is extracted by this session; graphify does not call any third party or read ANTHROPIC_API_KEY in-IDE.
    • Code-only refresh (no LLM, fast): run graphify update <path> — re-extracts the code AST deterministically, no model call. Prefer this when only code changed.
    • Gate: confirm graphify-out/graph.json and GRAPH_REPORT.md were written before reporting.
  4. Surface the highlights. Read graphify-out/GRAPH_REPORT.md and summarize into the output shape above — God Nodes, Surprising Connections, Suggested Questions — keeping the EXTRACTED/INFERRED/AMBIGUOUS labels. Point the user at graphify-out/graph.html for the interactive view.
  5. Offer the next move. Propose /graph-query "<question>" to explore (shortest paths, neighbors, communities), and — if the user wants it standing — graphify hook install for auto-rebuild on commit (a Cadence touch) or --watch for continuous rebuild while working.

Autonomy

L2 — drafts/refreshes the graph; the human reads it. Building is reversible and lands only in git-ignored graphify-out/, so it's safe to run on request. A code-only graphify update (deterministic, no LLM, no document pass) can run at L3 — e.g. via the commit hook — once trusted. Never commit graphify-out/; never widen scope beyond code + wiki/ without explicit approval.

Guardrails (from CLAUDE.md)

  • Never extract raw/ (or .env, .tmp/, secrets) — raw/ can hold pre-de-identified PHI/PII/financials. Document extraction is limited to the committed, de-identified wiki/. (Guardrails #1, #2, #7)
  • graphify-out/ is git-ignored — a derived artifact. No secrets, confidential figures, or sensitive data enter git via the graph.
  • Cite, don't invent. Carry graphify's honesty audit trail (EXTRACTED / INFERRED / AMBIGUOUS) into any claim about the graph. (Guardrail #6)
  • Code AST is parsed locally; the wiki document pass uses this host session only — no third-party call, no ANTHROPIC_API_KEY read.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.