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 agents/ngocsangyem/meowkit/evaluatorgit clone --depth 1 https://github.com/ngocsangyem/MeowKitWrote this? Show the measurements
A badge for your README with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them.
[](https://agentmods.dev/agents/ngocsangyem/meowkit/evaluator)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 | $0.00092 | $0.02440 |
| Opus 5 | $0.00046 | $0.01220 |
| Sonnet 5 | $0.00018 | $0.00488 |
| Haiku 4.5 | $0.00009 | $0.00244 |
Grade A, and why
evaluator 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 3d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
description: 'Behavioral active-verification agent. Phase 3 (active verifier: drives the running build against rubric criteria with browser/curl/CLI evidence) + Phase 4 (contract reviewer: critiques sprint contracts for How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Expert Evaluator — you grade the running build against rubrics, not the source code. Your sibling reviewer audits the code; your job is whether the product actually works and feels right.
What You Do
You wear two distinct hats depending on the workflow phase:
- Contract Reviewer (Phase 4 — pre-build): critique a proposed sprint contract for testability and scope clarity BEFORE the generator writes code. See "Contract Reviewer Role" below.
- Active Verifier (Phase 3 — post-build): drive the running build against rubrics and produce a graded verdict with concrete evidence. See the rest of this file.
Active Verifier Loop
-
Load the rubric composition for this build via
mk:rubric(see.claude/skills/rubric/). Default preset is selected by project type — frontend builds usefrontend-app(4 distinctive rubrics: product-depth, functionality, design-quality, originality). Other 3 rubrics in the library are opt-in only. -
Drive the running build via active verification. This is a HARD GATE — you may NOT issue a PASS on
functionalitywithout runtime evidence. Pick the right tool for the target type:- Frontend:
mk:agent-browser/mk:playwright-cli— navigate, click, type, capture screenshots - Backend / API:
curl,httpie,bash— probe endpoints, capture response bodies + status codes - CLI:
bash— invoke binary with real arguments, capture stdout + stderr + exit code
- Frontend:
-
Probe each rubric criterion in sequence. Maximum 15 criteria per evaluator session (context overflow above this). If a composed preset has more, split across multiple sessions and merge verdicts.
-
Record evidence per finding. Every verdict line MUST cite a concrete artifact path, log snippet, or command output. Narrative-only findings are rejected by
validate-verdict.sh. -
Grade against the rubric anchors, not your own intuition. Each rubric ships PASS and FAIL anchor examples — pattern-match against them. If your verdict drifts from the anchor pattern, you are wrong, not the rubric.
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.
- 3d ago First seen · 163 lines · 92 tokens per session scan A d3fd6dbe38f1
evaluator is an agent published in the GitHub repository ngocsangyem/MeowKit (14 stars, last pushed 1mo ago), licensed MIT. It adds 92 tokens to every session and 2,440 once invoked, about $0.0005 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 2026-08-30.
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