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/nerds-odd-e/doughnut/test-optimizationnpx skills add nerds-odd-e/doughnut --skill test-optimizationgit clone --depth 1 https://github.com/nerds-odd-e/doughnutWhat 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 | $0.00121 | $0.04129 |
| Opus 5 | $0.00060 | $0.02065 |
| Sonnet 5 | $0.00024 | $0.00826 |
| Haiku 4.5 | $0.00012 | $0.00413 |
Grade A, and why
test-optimization 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.
How it starts
The opening of the file, as written. The whole thing — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose: Systematic test-performance workflow for any sub-project (backend, frontend, cli, mcp-server, E2E).
Output: Optimized tests with per-slice commits + summary ending with
## TEST OPTIMIZATION COMPLETE.
When --resolve is given, skip every other step and go straight to
resolve_candidates.
Git does not use the Nix prefix. All other repo tooling does:
CURSOR_DEV=true nix develop -c …
Non-negotiable rules (every optimization pass):
- Remove or simplify redundant tests first — merge overlapping scenarios, drop duplicate setup, delete tests that only repeat coverage elsewhere.
- No fixed-time waits — no
sleep, nocy.wait(ms)without an assertion, no arbitrarysetTimeout/ debounce-timeout polling in unit tests. Use assertions, intercept aliases, fake timers, or API/testability setup. - Flaky is failure — re-run touched tests until stable; fix root cause, do not mask with retries.
Execution model: After writing the plan, always use execute-plan
(.agents/skills/execute-plan/SKILL.md). Coordinator delegates each group to a
fresh sub-agent; each slice runs post-change-refactor, then commits and pushes.
Do not accumulate context across slices in one agent.
E2E skip tag: @skipOptimizationDueToKnownNecessarySlowness on a Scenario
or Feature marks known-necessary slowness. Profile runs exclude it via
--expose tags=… (see profile). Adding the tag is a developer decision (Jidoka)
— propose only; do not add it yourself.
Candidates: .planning/test-optimization-blacklist.md holds Candidates
from optimization runs (proposals only). Keep that section; do not invent a
Skip list there.
Do not commit raw profile JSON (large, machine-specific). Gitignored paths:
e2e_test/reports/, .planning/*-profile-results.json,
.planning/quick/*-profile-results.json, ongoing/*-profile-results.json.
Goal: for each Candidate, decide whether the slow test earns its cost, or whether a cheaper test gives the same protection.
For each Candidate:
- Read the actual test (feature/scenario or unit test) plus the sibling scenarios in the same file and any backend/frontend unit tests the blacklist note references. Confirm what unique behavior it actually protects.
- Weigh the slow test against alternatives. Ask whether one or more unit tests (or a mocked E2E scenario) could give the same coverage, behavioral protection, and external user-value clarity. Remember: unit tests usually cannot reproduce the external user-value clarity of a genuine multi-step UI/PTY journey — so inherent-cost journeys stay as E2E.
- Distinguish inherent vs avoidable slowness. Cost from genuine product behavior (full page load, PDF/canvas render, PTY/Ink startup, frontend session state not replicable via API) is inherent. Cost from a live network call, redundant setup, or coverage duplicated elsewhere is avoidable — do not label avoidable cost as "necessary".
Resolve each Candidate with exactly one of:
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 · 351 lines · 121 tokens per session scan A 3424f677ba6e
test-optimization is a skill published in the GitHub repository nerds-odd-e/doughnut (49 stars, last pushed 2d ago), licensed MIT. It adds 121 tokens to every session and 4,129 once invoked, about $0.0006 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.
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