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/codagent-ai/agent-skills/test-plannpx skills add Codagent-AI/agent-skills --skill test-plangit clone --depth 1 https://github.com/Codagent-AI/agent-skillsWrote 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/codagent-ai/agent-skills/test-plan)<a href="https://agentmods.dev/skills/codagent-ai/agent-skills/test-plan"><img src="https://agentmods.dev/badge/skills/codagent-ai/agent-skills/test-plan.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 | $0.00062 | $0.01208 |
| Opus 5 | $0.00031 | $0.00604 |
| Sonnet 5 | $0.00012 | $0.00242 |
| Haiku 4.5 | $0.00006 | $0.00121 |
Grade A, and why
test-plan 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 4d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Plan
Create <change-dir>/test-plan.md after the proposal, specifications, and design are complete. The
plan records important automated integration and end-to-end obligations, authoritative agent
acceptance flows, and exceptional human-only checks. Specifications and implementation-time TDD remain
the source of unit-test requirements.
Do not write the plan until the user approves the proposed coverage. Use codagent:ask-questions for
consequential choices involving environments, external effects, cost, credentials, fidelity,
substitutes, or genuinely human-only judgment.
Plan coverage by risk
Read the definition artifacts, relevant repository instructions, current test structure, and affected public surfaces. Trace critical journeys and boundaries, then choose the lowest test layer that can reliably detect each important failure:
- Unit tests: the broad base for isolated logic, validation, transformations, decisions, and edge cases. Do not inventory these in the test plan.
- Integration tests (
INT-*): important boundaries where real components must work together, such as adapters, databases, filesystems, subprocesses, APIs, queues, or configuration-to-runtime wiring. Prefer controlled real dependencies or contract tests when they are more faithful than mocks. - Automated end-to-end tests (
E2E-*): a small set of critical journeys through a public entry point with realistic isolated setup and stable observable assertions.
Avoid fixed ratios, test-count quotas, duplicate assertions across layers, and E2E coverage for behavior a cheaper layer proves adequately. It is valid to record that no new integration or E2E obligation is warranted and explain why.
For each automated obligation, capture what it covers, the boundary or journey exercised, setup, stable assertions, constraints, and where it runs.
Define acceptance flows
Create concise AT-* obligations for human-style verification through the delivered UI, mobile
interface, TUI, CLI, API, library, or other public surface. Acceptance complements automated tests; it
does not rerun suites, enumerate edge cases, or fuzz inputs.
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.
- 4d ago First seen · 128 lines · 62 tokens per session scan A 9e5f33d027c7
test-plan is a skill published in the GitHub repository Codagent-AI/agent-skills (30 stars, last pushed 1mo ago), licensed MIT. It adds 62 tokens to every session and 1,208 once invoked, about $0.0003 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…