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 commands/fwornle/coding/kgbenchgit clone --depth 1 https://github.com/fwornle/codingWhat 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 | $0.00060 | $0.04573 |
| Opus 5 | $0.00030 | $0.02286 |
| Sonnet 5 | $0.00012 | $0.00915 |
| Haiku 4.5 | $0.00006 | $0.00457 |
Grade A, and why
kgbench scanned grade A with 1 finding 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s localhost:3032/api/kgbench/active-run # {"runId":null} when the coast is clear How it starts
The opening of the file, as written. The whole thing — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
kgbench (/kgbench) — run, resume, grade and diagnose the retrieval benchmark
Operator front-end for the coding-v1 code-retrieval benchmark: which retrieval strategy
answers questions about this repository best, at what token and latency cost.
This skill is a THIN WRAPPER. It shells to existing CLIs and reimplements no runner, grader, judge or report logic:
| Script | Role |
|---|---|
scripts/kgbench-supervise.sh |
detached, self-resuming matrix supervisor |
scripts/kgbench-run.mjs |
the matrix itself (--set --arms --only --reps --run-id) |
scripts/kgbench-regrade.mjs |
re-apply graders offline; --rejudge re-runs the judge |
scripts/kgbench-report.mjs |
render RESULTS.md + report.json (refuses to clobber hand-written files) |
scripts/kgbench-charts.mjs |
render the SVG figures |
scripts/kgbench-verify-questions.mjs |
validate questions and every evidence file:line |
scripts/kgbench-backfill-tokens.mjs |
re-resolve token fields offline; refuses a window narrower than the cell |
scripts/kgbench-repair-attempt-windows.mjs |
transitional: reconstruct per-attempt windows on runs recorded before the runner wrote them |
Read docs/benchmarks/measurement-lessons.md before changing a question, a matcher or an answer key. It records defects that cost a full investigation each, and one blind spot that makes the obvious diagnosis wrong.
Two front-ends, one benchmark
There is also a Performance → Benchmarks sub-tab at
localhost:3032/performance. It is a second front-end
over the same scripts, not a second implementation: its launcher shells to
kgbench-supervise.sh on the host, and its results view renders what
lib/kgbench/report.mjs produces — the function kgbench-report.mjs calls. A number shown
there and a number in the published report can differ only because the data changed.
CLI (/kgbench) |
Dashboard | |
|---|---|---|
| run / resume | ✅ | ✅ (Launch, and a resume offer when the id has cells) |
| watch a run | status |
✅ live monitor + supervisor log tail |
| cancel a run | Ctrl-C, or kill the group | ✅ Cancel |
| results | report → RESULTS.md |
✅ live aggregate, and the published artefacts |
| regrade / rejudge | ✅ | ❌ — CLI only, deliberately (Step 4) |
| publish | ✅ | ❌ — CLI only (Step 3) |
| doctor | ✅ | partial: a model probe, not the judge probe (Step 5) |
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.
- yesterday First seen · 323 lines · 60 tokens per session scan A 87a00b3df7cd
kgbench is a command published in the GitHub repository fwornle/coding (2 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 4,573 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.