| name | query-and-explain |
| description | Query an already-built graphify knowledge graph: natural-language questions, path-finding between two concepts, or explain a single node — without re-reading the source files. TRIGGERS - graphify query, ask the graph, what connects, path between concepts, explain node, query knowledge graph. |
| allowed-tools | Read, Bash, Glob, Grep |
Query & Explain the Graph
Self-Evolving Skill: This skill improves through use. If a query verb drifts or graph-interpretation guidance proves wrong — fix this file immediately, don't defer. Only update for real, reproducible issues.
Interrogate a persistent graphify-out/graph.json built earlier by graphify-tools:build-graph. This is the token-efficiency payoff: answers come from the graph (~71× fewer tokens on large corpora), not from re-reading raw files.
Prerequisite: a graphify-out/ directory must exist for the target corpus. If missing, invoke graphify-tools:build-graph first. If the corpus changed since the last build, suggest graphify <target> --update before trusting answers.
Verbs
Run from the directory containing graphify-out/ (or pass the target folder):
graphify query "what connects attention to the optimizer?"
graphify path "DigestAuth" "Response"
graphify explain "SwinTransformer"
Interpreting results
- Edge tags matter:
EXTRACTED = found in source; INFERRED = LLM-suggested; AMBIGUOUS = flagged uncertain. Quote the tag when relaying a claim to the operator.
- If
query returns nothing useful, check node naming with the graph's own inventory first — GRAPH_REPORT.md lists god nodes and communities; graph.html has interactive search.
- For symbol-level follow-ups (who calls this function, what breaks if I change it) hand off to the codegraph MCP tools instead — that's their home turf.
query/path/explain read graph.json locally — no LLM call, no backend needed. (Only extract/cluster-only/label hit an LLM; see ../../references/backends.md.)
Staleness check
find <target> -newer <target>/graphify-out/graph.json -type f | grep -v graphify-out | head
Post-Execution Reflection
After this skill completes, reflect before closing the task:
- Locate yourself. — Find this SKILL.md's canonical path before editing.
- What failed? — Fix the instruction that caused it.
- What worked better than expected? — Promote to recommended practice.
- What drifted? — Fix any script, reference, or dependency (esp.
references/backends.md) that no longer matches reality.
- Log it. — Add a dated note to the plugin CLAUDE.md provenance with trigger, fix, and evidence.
Do NOT defer. The next invocation inherits whatever you leave behind.