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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.

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SKILL.md

name refactor-150
description 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.

Refactor 150

Overview

Run in three stages:

  1. Research refactor options (iterative, no code changes).
  2. Plan + confirm + implement with tests and validation.
  3. Apply Scout105 cleanup (objective, small, user-approved).

Stage 1 — Research refactor options (iterative)

  1. Create or reuse investigation log at .temp/INVESTIGATION.md.

    • If the file does not exist, create it and add the template below.
    • Keep all research notes in this file only (no scattered notes in chat).
  2. 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.”
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. Stop before implementation.

    • End Stage 1 with: options summary, remaining unknowns, and a recommended path.

Investigation log template

# Investigation Log: <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

  1. Write a refactor plan.

    • Break into ordered steps with file-level granularity.
    • Include expected intermediate states (what should still pass after each step).
  2. List risks and edge cases.

    • Identify behavior changes, API contract risks, and hidden coupling.
    • Explicitly note any breaking-change risk.
  3. Define a validation checklist.

    • Tests to run (unit/integration).
    • Manual checks if needed (UI flows, API calls).
    • Expected outputs and what would indicate failure.
  4. 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.
  5. Ask for user confirmation before editing.

    • Provide plan, risks, and validation checklist.
    • Do not edit until the user approves.
  6. Implement the refactor.

    • Follow the plan in order.
    • Keep changes minimal and reversible.
  7. Add or update tests.

    • Cover changed logic and any new boundaries.
    • Avoid brittle tests; prefer behavior-based assertions.
  8. 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.