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/me2resh/apexyard/eval-agentsnpx skills add me2resh/apexyard --skill eval-agentsgit clone --depth 1 https://github.com/me2resh/apexyardWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/me2resh/apexyard/eval-agents)<a href="https://agentmods.dev/skills/me2resh/apexyard/eval-agents"><img src="https://agentmods.dev/badge/skills/me2resh/apexyard/eval-agents.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00044 | $0.06772 |
| Opus 5 | $0.00022 | $0.03386 |
| Sonnet 5 | $0.00009 | $0.01354 |
| Haiku 4.5 | $0.00004 | $0.00677 |
Grade A, and why
eval-agents 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 394 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/eval-agents — Review-Agent Eval Harness
Scores one of the framework's review agents (Rex / Hakim / Tariq) against a labeled corpus of real, already-reviewed PRs with frozen ground-truth defect sets. Reports catch-rate, false-positive-rate, and approve-precision (the headline metric) against a configurable pass/fail threshold.
Why this isn't an LLM-judge rating review prose
Spike #825 tested that shape first — score a review agent's text output against a 0-4 rubric, calibrated against recorded verdicts — and found it at chance on the one question that matters: was an approval justified? A fluent, verification-heavy wrong approval scored as well as or better than genuinely correct approvals (docs/spike-825/findings.md). This skill instead:
- Never asks a judge to rate review text. Ground truth is a frozen set of real defects, established once, offline, by a human, from actual re-review disagreements and confirmed fixes — never re-derived at run time, never established by the agent being measured.
- Runs the agent-under-test fresh against the corpus entry's diff, and mechanically/semantically compares its findings to the frozen defect set: caught / missed / false-alarm.
- Reports approve-precision as the headline metric — the rate at which the agent's approvals were actually justified. A missed BLOCKING/HIGH defect is an automatic WARN regardless of the aggregate score.
Full rationale: AgDR-0089. Corpus format: docs/eval-agents/SCHEMA.md.
Usage
/eval-agents rex # run against the seeded starter corpus
/eval-agents hakim --corpus docs/eval-agents/corpus/hakim.json
/eval-agents tariq --corpus my-corpus.json # tariq has no starter corpus — required
/eval-agents rex --check-only # validate corpus schema only, no spawns
<agent> is one of rex, hakim, tariq — the three review agents that produce a verdict over a diff and share the APPROVED / CHANGES REQUESTED / COMMENT vocabulary. Naqid is out of scope for v1 (it challenges premises, not diffs — no defect-set structure to score against; see AgDR-0089 § Decision point 7).
What ships with it
4 files 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.
- 4d ago First seen · 394 lines · 44 tokens per session scan A 77ab35775b39
eval-agents is a skill published in the GitHub repository me2resh/apexyard (498 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 6,772 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…