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/anastasiyaw/codex-claude-code-config/testing-strategynpx skills add AnastasiyaW/codex-claude-code-config --skill testing-strategygit clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-configWrote 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/anastasiyaw/codex-claude-code-config/testing-strategy)<a href="https://agentmods.dev/skills/anastasiyaw/codex-claude-code-config/testing-strategy"><img src="https://agentmods.dev/badge/skills/anastasiyaw/codex-claude-code-config/testing-strategy.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 | $0.00082 | $0.01728 |
| Opus 5 | $0.00041 | $0.00864 |
| Sonnet 5 | $0.00016 | $0.00346 |
| Haiku 4.5 | $0.00008 | $0.00173 |
Grade A, and why
testing-strategy 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 5d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing Strategy
Testing is an evidence-selection problem, not a contest to run the largest
suite. Choose the smallest set that can falsify the changed behavior, then add
one higher-level check only when it covers a boundary the lower level cannot.
Keep execution environments reusable, but separate their evidence profiles:
staging-smoke, security-proof, release-attestation, and nightly-stress.
Use harness-feedback when a gate is reported as overloaded or misplaced.
Workflow
- Freeze the acceptance criteria as observable outcomes.
- Inspect the changed files and classify the risk.
- Select the lowest useful test level from the matrix below and name the profile.
- Run the fast gate first. If it fails, fix the cause before adding more tests.
- Add a focused regression test for a confirmed bug or a changed invariant.
- Test real boundaries only when the change crosses them.
- Keep security-proof and release-attestation checks out of staging-smoke unless the acceptance criteria explicitly require that evidence.
- For high-risk or long-horizon work, use a fresh-context verifier and store the command, revision, result, and skipped checks in a durable artifact.
- When a verified stage becomes the input to another stage, seal that boundary
with commit/tree, contract, input/output digests, and a fresh verdict. Mark an
unavailable external prerequisite as
BLOCKED; do not rerun unrelated accepted code merely because the following environment is unavailable.
Compact Matrix
| Change | Required evidence | Usually deferred |
|---|---|---|
| Docs, comments, formatting only | Link/lint check when relevant | Runtime suite |
| Pure function, local refactor | Fast checks + focused unit/regression tests | Full E2E, mutation |
| Parser, serializer, file, DB, API adapter | Fast + focused + one real boundary/integration check | Browser E2E unless user flow changes |
| Auth, permissions, migrations, concurrency, public API, deployment | Fast + focused + integration/contract + targeted smoke; independent review for non-trivial changes | Full load test unless performance is in scope |
| UI or user journey | Fast + component/focused checks + one stable E2E smoke | Large browser matrix |
| Release or performance claim | All applicable lower levels + fixed benchmark/security/release evidence | Nothing that is part of the claim |
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.
- 5d ago First seen · 131 lines · 82 tokens per session scan A efefeae8c325
testing-strategy is a skill published in the GitHub repository AnastasiyaW/codex-claude-code-config (147 stars, last pushed today), licensed MIT. It adds 82 tokens to every session and 1,728 once invoked, about $0.0004 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
ai-content-filter
Professional Ai Content Filter Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
ai-engineer
Professional Ai Engineer skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
ai-product-manager
Professional Ai Product Manager Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
embedding-architect
Professional Embedding Architect skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
eval-harness
Professional Eval Harness Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
feature-engineer
Professional Feature Engineer skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.