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/yarlson/yarstack/test-designnpx skills add yarlson/yarstack --skill test-designgit clone --depth 1 https://github.com/yarlson/yarstackWhat 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 | $0.00540 |
| Opus 5 | $0.00022 | $0.00270 |
| Sonnet 5 | $0.00009 | $0.00108 |
| Haiku 4.5 | $0.00004 | $0.00054 |
Grade A, and why
test-design 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 — 28 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Design
Own the prospective test contract and test code, not the production implementation or retrospective evidence audit.
Workflow
- Confirm that dedicated automated tests are warranted. For engineering tooling and infrastructure, prefer native checks unless they cannot credibly prove important behavior, concrete complexity or failure risk warrants regression coverage, and a focused deterministic test boundary fits the task. If not, identify the applicable native checks and stop.
- Identify the authoritative contract, condition, action, observable result, invariants, important side effects, assumptions, and state preserved on failure.
- Choose the lowest test level that proves the contract through a stable public or system boundary.
- Match the method to the risk: use examples for concrete cases, property or model-based tests for invariants and sequences, fuzzing for broad or hostile input, and systematic concurrency or fault-injection tests for ordering, restart, and recovery. Select only methods that address a material risk.
- Make generated or scheduled cases reproducible with a recorded seed, useful bounds, and a minimized counterexample or retained failing input where the tooling supports them.
- Select only cases that materially define the behavior: normal operation, important boundaries, meaningful failures, cleanup, and external effects.
- Follow the repository's existing test structure, helpers, fixtures, and commands.
- Design test code to the same engineering standard as product code. Reuse existing focused helpers before adding new ones. Extract cohesive repeated setup while keeping scenario inputs and expected results visible. Prefer named table-driven cases when they share one setup, action, and assertion path; use direct tests when they do not.
- Write the smallest reproducible test whose failure identifies the broken contract.
- State what remains unverified when the behavior cannot be tested economically instead of adding a weak proxy assertion.
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 · 28 lines · 44 tokens per session scan A 78e74636fecb
test-design is a skill published in the GitHub repository yarlson/yarstack (3 stars, last pushed 4d ago), licensed MIT. It adds 44 tokens to every session and 540 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 2026-08-31.
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