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---
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"mattpocock-skills": minor
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---
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Add the **`research`** skill — a small, model-invoked skill that spins up a **background agent** to investigate a question against **primary sources** (official docs, source code, specs, first-party APIs), then leaves a single cited Markdown file wherever the repo keeps such notes. It's delegable reading legwork: you keep working while it reads, and get back a document to grill, plan, or design against. Listed in the top-level and Engineering READMEs (Model-invoked), added to `.claude-plugin/plugin.json`, given a docs page at `docs/engineering/research.md`, and routed as a Standalone in `ask-matt`.
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---
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"mattpocock-skills": patch
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---
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Reshape the `tdd` skill into reference-only. The red → green → refactor loop is anchored by leading words the model already holds, so the step-by-step Workflow was largely restating the loop and duplicating the horizontal-slicing anti-pattern. Dropped the Workflow and per-cycle checklist; folded their one durable idea — vertical slices / tracer bullets — into the Anti-patterns section and a short Rules-of-the-loop list. Introduced **seam** as the leading word for where tests go, collapsing the old Philosophy "public interfaces" prose and the Planning "confirm interface / behaviors" handshake into one rule: test only at pre-agreed seams, confirmed with the user before any test is written.
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Also dropped the refactor stage — TDD is now red → green, not red → green → refactor. Refactoring belongs to the review stage, not the implementation loop, so the refactor rule and `refactoring.md` were removed (its home is the `review` skill).
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@@ -11,6 +11,7 @@
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"./skills/engineering/to-issues",
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"./skills/engineering/to-prd",
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"./skills/engineering/prototype",
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"./skills/engineering/research",
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"./skills/engineering/domain-modeling",
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"./skills/engineering/codebase-design",
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"./skills/engineering/code-review",
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@@ -161,6 +161,7 @@ Skills I use daily for code work.
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- **[prototype](./skills/engineering/prototype/SKILL.md)** — Build a throwaway prototype to answer a design question — a runnable terminal app for state/logic questions, or several radically different UI variations toggleable from one route.
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- **[diagnosing-bugs](./skills/engineering/diagnosing-bugs/SKILL.md)** — Disciplined diagnosis loop for hard bugs and performance regressions: reproduce → minimise → hypothesise → instrument → fix → regression-test.
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- **[research](./skills/engineering/research/SKILL.md)** — Investigate a question against high-trust primary sources and capture the findings as a cited Markdown file in the repo, run as a background agent.
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- **[tdd](./skills/engineering/tdd/SKILL.md)** — Test-driven development with a red-green-refactor loop. Builds features or fixes bugs one vertical slice at a time.
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- **[domain-modeling](./skills/engineering/domain-modeling/SKILL.md)** — Actively build and sharpen a project's domain model — challenge terms against the glossary, stress-test with edge-case scenarios, and update `CONTEXT.md` and ADRs inline.
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- **[codebase-design](./skills/engineering/codebase-design/SKILL.md)** — Shared discipline and vocabulary for designing deep modules: a lot of behaviour behind a small interface, placed at a clean seam, testable through that interface.
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Quickstart:
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```bash
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npx skills add mattpocock/skills --skill=research
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```
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```bash
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npx skills update research
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```
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[Source](https://github.com/mattpocock/skills/tree/main/skills/engineering/research)
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## What it does
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`research` answers a question by reading the sources that own the answer and leaving a cited Markdown file behind. It works only from **primary sources** — official docs, source code, specs, first-party APIs — never a secondary write-up of them, so what it saves is traceable back to something authoritative rather than a summary of a summary.
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## When to reach for it
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Type `/research`, or the agent reaches for it automatically when a task turns into reading legwork.
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Reach for it when the next step is *finding something out* — how an API behaves, what a spec actually says, whether a claim holds — and you'd rather not stall your own thread doing the reading. For sharpening a plan by interview instead of by reading, use [grilling](https://aihero.dev/skills-grilling); for exploring what to build with throwaway code, use [prototype](https://aihero.dev/skills-prototype).
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## Delegated legwork
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The defining move is that the reading runs as a **background agent**. You keep working; it goes off, follows each claim back to its primary source, and drops a single cited Markdown file into wherever the repo keeps such notes. Research is legwork you delegate, not thinking you outsource — you get back a document to react to, with its sources attached.
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## Where it fits
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A reach-for-it-anytime standalone that feeds the thinking skills: the file it produces is something to grill, plan, or design against, so it sits upstream of work like [grilling](https://aihero.dev/skills-grilling) and [to-prd](https://aihero.dev/skills-to-prd) rather than in the build chain. For the whole map, see [ask-matt](https://aihero.dev/skills-ask-matt).
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@@ -21,6 +21,7 @@ Model- or user-reachable (rich trigger phrasing so the model can reach for them)
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- **[prototype](./prototype/SKILL.md)** — Build a throwaway prototype to answer a design question: a runnable terminal app for state/logic, or several toggleable UI variations.
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- **[diagnosing-bugs](./diagnosing-bugs/SKILL.md)** — Disciplined diagnosis loop for hard bugs and performance regressions: reproduce → minimise → hypothesise → instrument → fix → regression-test.
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- **[research](./research/SKILL.md)** — Investigate a question against high-trust primary sources and capture the findings as a cited Markdown file in the repo, run as a background agent.
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- **[tdd](./tdd/SKILL.md)** — Test-driven development with a red-green-refactor loop. Builds features or fixes bugs one vertical slice at a time.
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- **[domain-modeling](./domain-modeling/SKILL.md)** — Actively build and sharpen a project's domain model — challenge terms, stress-test with scenarios, update `CONTEXT.md` and ADRs inline.
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- **[codebase-design](./codebase-design/SKILL.md)** — Shared discipline and vocabulary for designing deep modules: small interfaces, clean seams, testable through the interface.
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- **`/grill-me`** — the same relentless interview as `/grill-with-docs`, but for when you have **no codebase**. Stateless: it saves nothing locally, builds no `CONTEXT.md`. Reach for it to sharpen any plan or design that doesn't live in a repo.
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- **`/prototype`** — a small, throwaway program that answers one design question: does this state model feel right, or what should this UI look like. Throwaway from day one — keep the answer, delete the code. It's the detour in step 2 of the main flow, but reach for it any time a design question is hard to settle on paper.
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- **`/research`** — delegate reading legwork to a **background agent**: it investigates a question against **primary sources**, then leaves a cited Markdown file in the repo. Keep working while it reads. The file it produces is something to take *into* the main flow at `/grill-with-docs` — research feeds the thinking, it doesn't replace it.
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- **`/teach`** — learn a concept over multiple sessions, using the current directory as a stateful workspace.
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- **`/writing-great-skills`** — reference for writing and editing skills well.
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---
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name: research
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description: Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
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---
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Spin up a **background agent** to do the research, so you keep working while it reads.
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Its job:
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1. Investigate the question against **primary sources** — official docs, source code, specs, first-party APIs — not a secondary write-up of them. Follow every claim back to the source that owns it.
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2. Write the findings to a single Markdown file, citing each claim's source.
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3. Save it where the repo already keeps such notes; match the existing convention, and if there is none, put it somewhere sensible and say where.
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@@ -5,107 +5,32 @@ description: Test-driven development. Use when the user wants to build features
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# Test-Driven Development
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## Philosophy
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TDD is the red → green loop. This skill is the reference that makes that loop produce tests worth keeping: what a good test is, where tests go, the anti-patterns, and the rules of the loop. Every section applies on every cycle — consult them before and during the loop, not after.
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**Core principle**: Tests should verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't.
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When exploring the codebase, read `CONTEXT.md` (if it exists) so test names and interface vocabulary match the project's domain language, and respect ADRs in the area you're touching.
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**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.
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## What a good test is
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**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.
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**Tautological tests** restate the implementation inside the assertion, so they pass by construction and give zero confidence. When the expected value is computed the way the code computes it — `expect(add(a, b)).toBe(a + b)`, snapshotting a figure you derived by hand the same way the code does, asserting a constant equals itself — the test can never disagree with the code: break the code wrong and the assertion breaks wrong with it. The expected value must come from an independent source of truth — a known-good literal, a worked example, the spec.
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Tests verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't. A good test reads like a specification — "user can checkout with valid cart" tells you exactly what capability exists — and survives refactors because it doesn't care about internal structure.
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See [tests.md](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines.
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## Anti-Pattern: Horizontal Slices
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## Seams — where tests go
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**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."
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A **seam** is the public boundary you test at: the interface where you observe behavior without reaching inside. Tests live at seams, never against internals.
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This produces **crap tests**:
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**Test only at pre-agreed seams.** Before writing any test, write down the seams under test and confirm them with the user. No test is written at an unconfirmed seam. You can't test everything — agreeing the seams up front is how testing effort lands on the critical paths and complex logic instead of every edge case.
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- Tests written in bulk test _imagined_ behavior, not _actual_ behavior
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- You end up testing the _shape_ of things (data structures, function signatures) rather than user-facing behavior
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- Tests become insensitive to real changes - they pass when behavior breaks, fail when behavior is fine
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- You outrun your headlights, committing to test structure before understanding the implementation
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Ask: "What's the public interface, and which seams should we test?"
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**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.
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## Anti-patterns
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```
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WRONG (horizontal):
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RED: test1, test2, test3, test4, test5
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GREEN: impl1, impl2, impl3, impl4, impl5
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- **Implementation-coupled** — mocks internal collaborators, tests private methods, or verifies through a side channel (querying the database instead of using the interface). The tell: the test breaks when you refactor but behavior hasn't changed.
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- **Tautological** — the assertion recomputes the expected value the way the code does (`expect(add(a, b)).toBe(a + b)`, a snapshot derived by hand the same way, a constant asserted equal to itself), so it passes by construction and can never disagree with the code. Expected values must come from an independent source of truth — a known-good literal, a worked example, the spec.
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- **Horizontal slicing** — writing all tests first, then all implementation. Bulk tests verify _imagined_ behavior: you test the _shape_ of things rather than user-facing behavior, the tests go insensitive to real changes, and you commit to test structure before understanding the implementation. Work in **vertical slices** instead — one test → one implementation → repeat, each test a **tracer bullet** that responds to what the last cycle taught you.
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RIGHT (vertical):
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RED→GREEN: test1→impl1
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RED→GREEN: test2→impl2
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RED→GREEN: test3→impl3
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...
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```
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## Rules of the loop
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## Workflow
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### 1. Planning
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When exploring the codebase, read `CONTEXT.md` (if it exists) so that test names and interface vocabulary match the project's domain language, and respect ADRs in the area you're touching.
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Before writing any code:
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- [ ] Confirm with user what interface changes are needed
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- [ ] Confirm with user which behaviors to test (prioritize)
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- [ ] Identify opportunities for deep modules (small interface, deep implementation) — run the `/codebase-design` skill for the vocabulary and the testability checks
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- [ ] List the behaviors to test (not implementation steps)
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- [ ] Get user approval on the plan
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Ask: "What should the public interface look like? Which behaviors are most important to test?"
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**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.
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### 2. Tracer Bullet
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Write ONE test that confirms ONE thing about the system:
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```
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RED: Write test for first behavior → test fails
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GREEN: Write minimal code to pass → test passes
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```
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This is your tracer bullet - proves the path works end-to-end.
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### 3. Incremental Loop
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For each remaining behavior:
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```
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RED: Write next test → fails
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GREEN: Minimal code to pass → passes
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```
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Rules:
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- One test at a time
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- Only enough code to pass current test
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- Don't anticipate future tests
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- Keep tests focused on observable behavior
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### 4. Refactor
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After all tests pass, look for [refactor candidates](refactoring.md):
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- [ ] Extract duplication
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- [ ] Deepen modules (move complexity behind simple interfaces)
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- [ ] Apply SOLID principles where natural
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- [ ] Consider what new code reveals about existing code
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- [ ] Run tests after each refactor step
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**Never refactor while RED.** Get to GREEN first.
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## Checklist Per Cycle
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```
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[ ] Test describes behavior, not implementation
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[ ] Test uses public interface only
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[ ] Test would survive internal refactor
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[ ] Expected values are independent literals, not recomputed from the code
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[ ] Code is minimal for this test
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[ ] No speculative features added
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```
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- **Red before green.** Write the failing test first, then only enough code to pass it. Don't anticipate future tests or add speculative features.
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- **One slice at a time.** One seam, one test, one minimal implementation per cycle.
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- **Refactoring is not part of the loop.** It belongs to the review stage (see the `review` skill), not the red → green implementation cycle.
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# Refactor Candidates
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After TDD cycle, look for:
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- **Duplication** → Extract function/class
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- **Long methods** → Break into private helpers (keep tests on public interface)
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- **Shallow modules** → Combine or deepen
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- **Feature envy** → Move logic to where data lives
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- **Primitive obsession** → Introduce value objects
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- **Existing code** the new code reveals as problematic
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Reference in New Issue
Block a user