Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/lagrahhn/codegraph-branch/agent-evalnpx skills add lagrahhn/codeGraph-branch --skill agent-evalgit clone --depth 1 https://github.com/lagrahhn/codeGraph-branchWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00065 | $0.00911 |
| Opus 5 | $0.00032 | $0.00456 |
| Sonnet 5 | $0.00013 | $0.00182 |
| Haiku 4.5 | $0.00006 | $0.00091 |
Grade A, and why
agent-eval scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
92% identical to agent-eval — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CodeGraph Quality Audit
Measures how much CodeGraph helps an agent versus plain grep/read, for a chosen
codegraph version on a chosen real-world repo. Drives the harness in
scripts/agent-eval/.
Prerequisites
tmux3+, a logged-inclaudeCLI,node,git(macOS/Linux).- Run from the codegraph repo root.
Workflow
Copy this checklist:
- [ ] 1. Pick version (local or npm)
- [ ] 2. Pick language
- [ ] 3. Pick repo by size
- [ ] 4. Pick harness (headless / tmux / both)
- [ ] 5. Run audit.sh in the background
- [ ] 6. Report results
Step 1 — version. Ask with AskUserQuestion: which codegraph version to test.
Offer "Local dev build" and "Latest published"; the free-text "Other" lets the
user type a specific version (e.g. 0.7.10). Map the answer to a VERSION token:
- "Local dev build" →
local - "Latest published" →
latest - a typed version → that string (e.g.
0.7.10)
Step 2 — language. Read .claude/skills/agent-eval/corpus.json. Ask with
AskUserQuestion which language to test, listing the languages that have entries.
Step 3 — repo. From the chosen language's entries, ask which repo. Label each
option with its size and file count, e.g. excalidraw — Medium (~600 files).
Each entry carries the repo URL and a representative question.
Step 4 — harness. Ask with AskUserQuestion which harness to run, and map
the answer to a MODE token:
- "Headless" →
headless—claude -pwith stream-json: exact tokens/cost and a clean tool sequence (2 runs, fast, no TTY). - "Interactive (tmux)" →
tmux— drives the real Claude TUI in tmux: faithful Explore-subagent behavior, metrics from session logs (2 runs, slower). - "Both" →
all— headless + interactive (4 runs).
Step 5 — run. Launch in the background (sets the version, clones if missing, wipes + re-indexes, runs the chosen arms — several minutes):
scripts/agent-eval/audit.sh <VERSION> <repo-name> <repo-url> "<question>" <MODE>
Step 6 — report. When the job finishes, read the log and report per arm:
- Headless (
parse-run.mjs): total tool calls, fileReads, Grep/Bash, codegraph-tool calls, duration, total cost. - Interactive (
parse-session.mjs): theVERDICT: codegraph_explore used Nx | Read N | Grep/Bash NandTOKENS:lines.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 75 lines · 65 tokens per session scan A b83c65193e06
agent-eval is a skill published in the GitHub repository lagrahhn/codeGraph-branch (2 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 911 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to agent-eval, differing in 6 lines, and is treated as a copy.
Other skills, from other repositories
graph
Whole-codebase structural map of the codanna index as one self-contained HTML disc. Wedges per top-level module, concentric rings with hubs at the centre, hover or click a symbol to light its edge web, search, hide or highlight modules, brush a date range on the ribbon timeline (symbols dated by git blame), heatmap of…
x-ray
Deep codebase exploration using semantic search and relationship mapping. Use when you need to understand the current codebase.
brainctl
Unified agent memory CLI — read, write, search, and maintain the shared memory spine (brain.db). Use for persistent cross-session memory, knowledge graph, event logging, decisions, affect tracking, and consolidation.
adding-a-language
How a new language enters Kivgraph's graph - the two routes and why one of them is almost always wrong, the four decisions that cannot be migrated later, the branches that decide what your language is without asking, and the gates that fail closed. Use when adding or extending language support, when touching…
codestory-grounding
Use when an agent should ground a local repository with CodeStory before making source claims, planning edits, choosing tests, reviewing changes, or using broad retrieval evidence through the CodeStory plugin MCP.
running-tests
Cómo se ejecutan y se escriben los tests de Kivgraph - las tres suites, el tag ladybug que no se invoca a mano, qué se salta y por qué, y el smoke test del binario. Usar al correr tests, al añadirlos, ante un fallo de enlazado library 'lbug' not found, ante un SKIP inesperado, o antes de cerrar una tarea.