Individual skill
knowledge-graph
Build, refresh and query a deterministic code knowledge graph to cut orientation-token cost. Triggers: knowledge graph, graphify, code graph, god nodes, orientation cost, map the codebase, what connects, callers of, blast radius.
plugins/ariaxhan/kernel-claude/skills/knowledge-graph/SKILL.md
Source commit d780783eba4ecc7c8b9429f95c9362df95f07c61
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 4, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 1,531
- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-coding Repository topic
- awesome Repository topic
- awesome-list Repository topic
- codex Repository topic
- codex-plugins Repository topic
- openai Repository topic
- codex-skill Repository topic
- codex-skills Repository topic
- marketplace Repository topic
- codex-marketplace Repository topic
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
Read excerpt
<skill id="knowledge-graph">
<purpose>
An agent's token bill splits into ORIENTATION (finding where the answer lives — reading
files, following imports, grepping) and REASONING (actually solving). On a large, tangled
repo the orientation half dominates, and it is pure overhead: the model is not thinking yet,
it is still navigating. A pre-built code knowledge graph replaces that file-crawl with one
query, so you pay orientation tokens once (at build) instead of every session.
The saving is CONDITIONAL on repo size × tangle, not a fixed multiplier. Measured on real
repos: ~5.7x fewer tokens/query on a mid-size service, ~73x on a large interconnected one,
~13% on a tiny library. The graph query cost is ~constant; naive full-corpus cost scales with
size — so reduction = corpus ÷ constant. Do the arithmetic on YOUR repo, don't quote a headline.