跳到正文
cccskills
免费在 GitHub 公开

tdd

Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development.

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(6)

  • SKILL.md4.8 KB
  • deep-modules.md1.2 KB
  • interface-design.md653 B
  • mocking.md1.4 KB
  • refactoring.md387 B
  • tests.md1.7 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Test-Driven Development

Philosophy

Follow the repository's Test Strategy gate before starting a red-green cycle. TDD controls the order of work; it does not make every change or behavior worth a test. If the proposed assertion would lock copy, markup, prompt prose, configuration inventory, or another non-contract, stop without creating RED.

Core principle: Tests should verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't.

Good tests are integration-style: they exercise real code paths through public APIs. They describe what the system does, not how it does it. A good test reads like a specification - "user can checkout with valid cart" tells you exactly what capability exists. These tests survive refactors because they don't care about internal structure.

Bad tests are coupled to implementation. They mock internal collaborators, test private methods, or verify through external means (like querying a database directly instead of using the interface). The warning sign: your test breaks when you refactor, but behavior hasn't changed. If you rename an internal function and tests fail, those tests were testing implementation, not behavior.

See tests.md for examples and mocking.md for mocking guidelines.

Anti-Pattern: Horizontal Slices

DO NOT write all tests first, then all implementation. This is "horizontal slicing" - treating RED as "write all tests" and GREEN as "write all code."

This produces crap tests:

  • Tests written in bulk test imagined behavior, not actual behavior
  • You end up testing the shape of things (data structures, function signatures) rather than user-facing behavior
  • Tests become insensitive to real changes - they pass when behavior breaks, fail when behavior is fine
  • You outrun your headlights, committing to test structure before understanding the implementation

Correct approach: Vertical slices via tracer bullets. One test → one implementation → repeat. Each test responds to what you learned from the previous cycle. Because you just wrote the code, you know exactly what behavior matters and how to verify it.

WRONG (horizontal):
  RED:   test1, test2, test3, test4, test5
  GREEN: impl1, impl2, impl3, impl4, impl5

RIGHT (vertical):
  RED→GREEN: test1→impl1
  RED→GREEN: test2→impl2
  RED→GREEN: test3→impl3
  ...

Workflow

1. Planning

When exploring the codebase, use the project's domain glossary so that test names and interface vocabulary match the project's language, and respect ADRs in the area you're touching.

Before writing any code:

  • Confirm with user what interface changes are needed
  • Confirm with user which behaviors to test (prioritize)
  • Identify opportunities for deep modules (small interface, deep implementation)
  • Design interfaces for testability
  • Select the smallest set of costly, materially distinct regressions not already covered
  • Get user approval on the plan

Ask: "What should the public interface look like? Which behaviors are most important to test?"

You can't test everything. Confirm with the user exactly which behaviors matter most. Focus testing effort on critical paths and complex logic, not every possible edge case.

2. Tracer Bullet

Write ONE test that confirms ONE thing about the system:

RED:   Write test for first behavior → test fails
GREEN: Write minimal code to pass → test passes

This is your tracer bullet - proves the path works end-to-end.

3. Incremental Loop

For each remaining high-value behavior:

RED:   Write next test → fails
GREEN: Minimal code to pass → passes

Rules:

  • One test at a time
  • Only enough code to pass current test
  • Don't anticipate future tests
  • Keep tests focused on observable behavior
  • Stop when the tracer bullet and materially distinct failure modes are covered

4. Refactor

After all tests pass, look for refactor candidates:

  • Extract duplication
  • Deepen modules (move complexity behind simple interfaces)
  • Apply SOLID principles where natural
  • Consider what new code reveals about existing code
  • Run tests after each refactor step

Never refactor while RED. Get to GREEN first.

Checklist Per Cycle

[ ] Test describes behavior, not implementation
[ ] Test uses public interface only
[ ] Test would survive internal refactor
[ ] Test would fail because the product got worse, not because wording or configuration changed
[ ] Code is minimal for this test
[ ] No speculative features added

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Plan and use user-consented local camera and microphone observations for an explicitly authorized physical target. Use when a capture can establish a bounded physical-state observation such as whether a test fixture changed state, an instrument reading changed, or equipment noise changed relatively.

中文简介正在准备中。当前显示原文说明。

justsml/ExploitHunter.app142026年10月17日 更新

Plan vulnerability research using conventional bug-hunting and pentest stage names, specialty playbooks, and a research-hypothesis-experiment loop. Use when designing a bug bounty workflow, selecting tools and strategies, building a decision tree, or turning a target/scope into a staged hunting plan.

中文简介正在准备中。当前显示原文说明。

justsml/ExploitHunter.app142026年10月17日 更新

Passive code-review lane for authorized repositories, local checkouts, uploaded source archives, and diffs. Use when the security research agent needs deterministic candidate discovery before expensive AI investigation, scoped PR-style review, append-only evidence records, or independent revalidation of code findings.

中文简介正在准备中。当前显示原文说明。

justsml/ExploitHunter.app142026年10月17日 更新

Run independent, task-matched expert attempts, select a base, and synthesize the strongest result.

中文简介正在准备中。当前显示原文说明。

justsml/ExploitHunter.app142026年10月17日 更新

Select established CTF and security-research tools for authorized artifact triage, web inspection, reversing, crypto, forensics, networking, and exploit validation. Use when a user provides a CTF-style tool catalog, asks which tools to use, or needs safe usage instructions for common offensive/security tools.

中文简介正在准备中。当前显示原文说明。

justsml/ExploitHunter.app142026年10月17日 更新

diagnose

免费

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

中文简介正在准备中。当前显示原文说明。

justsml/ExploitHunter.app142026年10月17日 更新

查看 justsml 的全部技能

报告此技能的问题