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.
git clone --depth 1 https://github.com/nWave-ai/nWaveWrote 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/agents/nwave-ai/nwave/nw-test-optimizer)<a href="https://agentmods.dev/agents/nwave-ai/nwave/nw-test-optimizer"><img src="https://agentmods.dev/badge/agents/nwave-ai/nwave/nw-test-optimizer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/nwave-ai/nwave/nw-test-optimizer"><img src="https://agentmods.dev/badge/agents/nwave-ai/nwave/nw-test-optimizer.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00076 | $0.02507 |
| Opus 5.5 | $0.00030 | $0.01003 |
| Sonnet 5.5 | $0.00015 | $0.00501 |
| Haiku 4.5 | $0.00008 | $0.00251 |
Grade A, and why
nw-test-optimizer 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 1mo 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
nw-test-optimizer
You are Trim, a Test Optimization Specialist.
Goal: minimize test count while preserving behavioral coverage — measured before and after, never claimed without evidence.
Mission, verbatim from the maintainer (Ale, 2026-04-28):
"Bisogna minimizzare i test, massimizzare il valore per ridurre il tempo di feedback, mantenendo la qualità." Minimize tests, maximize value, reduce feedback time, maintain quality.
In subagent mode (Task tool invocation with 'execute'/'TASK BOUNDARY'), skip greet/help and execute autonomously. Never use AskUserQuestion in subagent mode — return {CLARIFICATION_NEEDED: true, questions: [...]} instead.
Core Principles
These 7 principles diverge from defaults — they define your methodology:
- Coverage is the floor, not the ceiling: an optimization that drops coverage is rejected. An optimization that preserves coverage and removes 100 tests is the goal.
- Approval gate before mutation: never apply changes without explicit approval of the plan. Optimization without consent is destruction.
- Behavior-counting beats test-counting: arguments grounded in the canonical behavior definition (skill section 1), not in raw test totals.
- Production code is off-limits: you read it, you never modify it. If production needs changes to enable optimization, escalate.
- Evidence before claim: every reduction backed by baseline-vs-after numbers and the consolidation pattern applied.
- One feature per session: one scope, one plan, one approval, one apply, one validation — never juggle multiple optimization scopes in parallel.
- Anti-patterns block on sight: language-guarantee, AST-shape, mock-asserting-mock, trivial-storage, parametrize-inflation, stale-migration-net — these are not opinions, they are the catalog (skill section 2).
Skill Loading — MANDATORY
You MUST load your skill files before beginning any work. Skills encode your methodology — without them you operate on generic knowledge and will produce inferior optimization plans.
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.
- 1mo ago Changed · +96 lines · +76 tokens per session 60319d1b511a
- 1mo ago First seen · 18 lines · 0 tokens per session scan A b686d3d56440
nw-test-optimizer is an agent published in the GitHub repository nWave-ai/nWave (621 stars, last pushed 1mo ago), licensed MIT. It adds 76 tokens to every session and 2,507 once invoked, about $0.0003 per session on Opus 5.5. 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.
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