Graph
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".From its SKILL.md
npx -y skills add alirezarezvani/gaios --skill graphAssembled 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.
SKILL.md
5.4 KB, ~1.3k tokens by cl100k_base, 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
/wikiloop that added entries — to refresh the picture. - As a thinking aid before a refactor, an audit, or a
/weeklyreview: 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
- Ensure graphify is installed. Run
python tools/graphify_setup.py check. If missing, offer to install (uv tool install graphifyy, fallbackpipx install graphifyy/pip install graphifyy, thengraphify install --platform claude). No account or signup is needed. Gate: don't proceed untilgraphify --versionresolves. - Set the build scope — code + committed
wiki/ONLY. This is the hard line:- Include: source code (Python in
tools/, etc.) and the committedwiki/. - 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 atraw/. - 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.
- Include: source code (Python in
- 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 inwiki/is extracted by this session; graphify does not call any third party or readANTHROPIC_API_KEYin-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.jsonandGRAPH_REPORT.mdwere written before reporting.
- Full build (code + wiki): the heavy document pass runs through graphify's own pipeline using the host IDE session — invoke
- Surface the highlights. Read
graphify-out/GRAPH_REPORT.mdand summarize into the output shape above — God Nodes, Surprising Connections, Suggested Questions — keeping the EXTRACTED/INFERRED/AMBIGUOUS labels. Point the user atgraphify-out/graph.htmlfor the interactive view. - Offer the next move. Propose
/graph-query "<question>"to explore (shortest paths, neighbors, communities), and — if the user wants it standing —graphify hook installfor auto-rebuild on commit (a Cadence touch) or--watchfor 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-identifiedwiki/. (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_KEYread.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.