academic-paper-reviewe…
Simulates academic peer review, evaluating papers across Originality, Methodology, Results, and Writing to provide Major/Minor…
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.
Claude Code
$ npx -y skills add zebbern/claude-code-guide --skill test-driven-dev --agent claude-code
Codex
$ npx skills add zebbern/claude-code-guide --skill test-driven-dev -a codex -y
Cursor
$ npx skills add zebbern/claude-code-guide --skill test-driven-dev -a cursor -y
Gemini CLI
$ npx skills add zebbern/claude-code-guide --skill test-driven-dev -a gemini-cli -y
GitHub Copilot
$ npx skills add zebbern/claude-code-guide --skill test-driven-dev -a github-copilot -y
OpenCode
$ npx skills add zebbern/claude-code-guide --skill test-driven-dev -a opencode -y
Windsurf
$ npx skills add zebbern/claude-code-guide --skill test-driven-dev -a windsurf -y
name: test-driven-dev description: 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.
**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](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines.
**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**:
**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 ...
Before writing any code:
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.
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.
For each remaining behavior:
RED: Write next test → fails GREEN: Minimal code to pass → passes
Rules:
After all tests pass, look for [refactor candidates](refactoring.md):
**Never refactor while RED.** Get to GREEN first.
[ ] Test describes behavior, not implementation [ ] Test uses public interface only [ ] Test would survive internal refactor [ ] Code is minimal for this test [ ] No speculative features added
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