Claude-skill-registry 52-execute-refactor-150
[52] EXECUTE. Three-stage refactoring workflow: (1) iterative research of refactor/modularization options, (2) plan + risk/edge-case analysis + Scope150 validation, then implement with tests after user confirmation, and (3) apply Scout105 cleanup protocol. Use when asked to refactor, modularize, or restructure code safely.
git clone https://github.com/majiayu000/claude-skill-registry
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/52-execute-refactor-150" ~/.claude/skills/majiayu000-claude-skill-registry-52-execute-refactor-150 && rm -rf "$T"
skills/data/52-execute-refactor-150/SKILL.mdExecute-Refactor 150 Protocol
Overview
Run in three stages:
- Research refactor options (iterative, no code changes).
- Plan + confirm + implement with tests and validation.
- Apply Scout105 cleanup (objective, small, user-approved).
Stage 1 — Research refactor options (iterative)
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Create or reuse the session log at
..sessions/SESSION_[date]-[name].md- If the file does not exist, create it and add the investigation template below.
- Keep all research notes inside the session log only (no scattered notes in chat).
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Define the core question (the refactor goal).
- Write a single sentence: “We need to refactor X to achieve Y.”
- Example: “Refactor SermonCard to reduce duplication and isolate date logic.”
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Define scope (Scope150).
- Core (100%): list files and behaviors you will directly change.
- Boundary (50%): list callers, dependent modules, tests, configs, and data flow.
- If unsure, add a “to verify” bullet and resolve it during observations.
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Perform observations (search/read) in ordered layers.
- Interface layer: find entry points (routes, public APIs, UI entry points).
- Domain layer: identify entities, i18n keys, enums, types.
- Pattern layer: locate hooks, services, clients, shared utilities.
- Usage layer: trace imports and call sites.
- For each layer, read the minimum number of files that explain the behavior.
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Record findings in the log with sources.
- Each fact must include a source (file path + line reference or command).
- Separate facts from hypotheses. Do not mix them.
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Generate hypotheses and refactor options.
- For each option, note: goal, steps, benefits, risks, and test impact.
- Prefer at least 2 options so tradeoffs are explicit.
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Decide if more research is needed.
- If user says “research more”, expand scope or inspect new files.
- Update the log with new branches and continue Stage 1.
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Stop before implementation.
- End Stage 1 with: options summary, remaining unknowns, and a recommended path.
Investigation log template
## Investigations ### Investigation: <short topic> #### Core question - ... #### Scope - Core (100%): - ... - Boundary (50%): - ... #### Findings - <fact> (source: file path / command) - Subfinding #### Hypotheses - H1: ... - Prediction: ... - Test: ... - Status: pending/confirmed/rejected #### Refactor options - Option A: ... (pros/cons) - Option B: ... (pros/cons) #### Next branches - ...
Stage 2 — Plan, confirm, implement
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Write a refactor plan.
- Break into ordered steps with file-level granularity.
- Include expected intermediate states (what should still pass after each step).
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List risks and edge cases.
- Identify behavior changes, API contract risks, and hidden coupling.
- Explicitly note any breaking-change risk.
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Define a validation checklist.
- Tests to run (unit/integration).
- Manual checks if needed (UI flows, API calls).
- Expected outputs and what would indicate failure.
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Perform Scope150 validation planning.
- Core (100%): ensure each planned change has a test or validation step.
- Boundary (50%): list all callers/integrations/tests to be checked.
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Ask for user confirmation before editing.
- Provide plan, risks, and validation checklist.
- Do not edit until the user approves.
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Implement the refactor.
- Follow the plan in order.
- Keep changes minimal and reversible.
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Add or update tests.
- Cover changed logic and any new boundaries.
- Avoid brittle tests; prefer behavior-based assertions.
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Run validation.
- Execute all tests from the checklist.
- Record results and fix failures before moving to Stage 3.
Stage 3 — Scout105 cleanup protocol
Apply only objective cleanup after a Key Point (phase complete). Do not add features.
Trigger (Key Point)
- Apply only after a milestone where the user would see complete value.
- Do not run per-file; run once per phase.
Allowed cleanup categories (objective only)
- Unused code: unused imports/vars/fields (provable by grep/IDE).
- Typos: spelling errors in comments/strings (spellcheckable).
- Formatting inconsistencies: breaks the file’s own pattern.
- Dead code: commented debug lines or unreachable code.
- Obviously wrong logic: provably incorrect (duplicate checks, impossible types).
Constraints
- Only in files already touched by the primary task.
- Remove garbage only; no new features or refactors.
- Each cleanup must take ≤ 30 seconds to verify + fix.
- Total cleanup time ≤ 5% of primary task time.
- Must be objectively measurable; if not measurable, skip.
- Require user approval before executing cleanup.
Scout105 report (present to user)
✅ Key Point complete: <brief summary> Scout105 opportunities: - <file>: <item> (category, evidence) - <file>: <item> (category, evidence) Run Scout105 cleanup? [Yes / Skip / Selective]
Execution
- If approved, apply all selected cleanups in batch.
- Run tests/build to validate no regression.
- If failures occur, revert or investigate causality before proceeding.
Output expectations
- Stage 1: Provide refactor options + log path + remaining branches + recommended path.
- Stage 2: Provide plan, risks, validation checklist, and request confirmation.
- Stage 3: Provide Scout105 report, decision, and validation result.