dry-consolidation

# DRY Consolidation Systematic extraction of duplicated code into shared, tested abstractions. ## When to Use This Skill | Use this skill when... | Use these instead when... | |------------------------|--------------------------| | Multiple files have identical/near-identical code blocks | Single file needs cleanup → `/code:refactor` | | Copy-pasted utility functions across components | Looking for anti-patterns without fixing → `/code:antipatterns` | | Repeated UI patterns (dialogs, pagination, error states) | Functional refactoring of a file or directory → `/code:refactor` | | Duplicated hooks or state management boilerplate | Structural code search only → `ast-grep-search` | | Near-duplicate copy-paste with renamed vars needs enumerating (jscpd finds the clusters here) | Matching one known structural pattern → `ast-grep-search` | | Import blocks are bloated from repeated inline patterns | Linting/formatting issues → `/lint:check` | ## Context - Target path: !`echo "$1"` - Project type: !`find . -maxdepth 1 \( -name "package.json" -o -name "Cargo.toml" -o -name "pyproject.toml" -o -name "go.mod" \)` - Source directories: !`find . -maxdepth 1 -type d \( -name "src" -o -name "lib" -o -name "app" -o -name "components" -o -name "packages" \)` - Test framework: !`find . -maxdepth 2 \( -name "vitest.config.*" -o -name "jest.config.*" -o -name "pytest.ini" -o -name "conftest.py" \)` - Existing shared utilities: !`find . \( -path "*/lib/*" -o -path "*/utils/*" -o -path "*/shared/*" -o -path "*/common/*" -o -path "*/hooks/*" \) -type f -print -quit` ## Parameters - `$1`: Path or directory to scan (defaults to `src/`) - `--scope`: Focus on a specific extraction type: `utilities`, `components`, `hooks`, or `all` (default: `all`) - `--dry-run`: Analyze and report duplications without making changes ## Execution Execute this 7-step consolidation workflow. Track each extraction as a separate task with `TodoWrite` when the session has the task tools (see `.claude/rules/agentic-permissions.md` § Task-tool availability), otherwise as a checklist in your response. ### Step 1: Discover duplicate clusters (deterministic clone detection) Enumerate duplicate ranges with a deterministic clone detector, then read **only the reported ranges** — not whole candidate files. This keeps discovery reproducible and cheap. Token-based detection (jscpd) finds copy-paste independent of whitespace/formatting and of the enclosing symbol name — clone pairs a name-based Grep misses when the wrapping function is renamed. ast-grep (1b) then adds tolerance for variables renamed *inside* the block. #### 1a. Token-based near-duplicates with jscpd `jscpd` is a token-based copy/paste detector that supports 150+ languages despite the "js" in the name; `npx` runs it with no global install. Run it over the target path: ```bash npx jscpd --reporters json --min-tokens 50 --output /tmp/jscpd-dry --silent <path> ``` It writes `/tmp/jscpd-dry/jscpd-report.json`. Read that report and parse its `duplicates` array — each entry gives the exact file/line ranges of a clone pair plus its size in tokens/lines: ```json { "duplicates": [ { "format": "tsx", "lines": 12, "tokens": 84, "firstFile": { "name": "src/UserList.tsx", "start": 20, "end": 32 }, "secondFile": { "name": "src/OrderList.tsx", "start": 15, "end": 27 } } ], "statistics": { "total": { "clones": 3, "duplicatedLines": 40, "duplicatedTokens": 252, "percentage": 5.1 } } } ``` For each reported clone, **Read only the line ranges** (`Read` with `offset`/`limit` around `start`/`end`) to confirm the duplication and classify it — do not Read whole candidate files. jscpd similarity is high by construction for a reported clone (a `--min-tokens` match); note the tokens/lines for the Extraction Plan. #### 1b. Structural confirmation with ast-grep Once jscpd surfaces a cluster, confirm it is the same *shape* — same call-shape / same block modulo captured variables — with ast-grep metavariables. `$VAR` / `$INIT` match any identifier/expression, so a block differing only in renamed captures still matches: ```bash ast-grep -p 'const $VAR = useState($INIT)' --lang tsx <path> ``` Use this to separate a genuine extractable duplicate from a coincidental token overlap before planning the extraction. (For a standalone structural search without extraction, use the `ast-grep-search` skill.) #### 1c. Graceful fallback (Grep) when the detector is unavailable When `npx`/`jscpd` is unavailable, or the ecosystem has no `npx` on PATH, fall back to agent-driven text search: 1. Use Grep to find repeated function names, variable patterns, and import clusters 2. Use Glob to identify files with similar structure (e.g., all `*List.tsx`, all `*Detail.tsx`) 3. Read candidate files to confirm duplication and measure scope This fallback has lower recall for near-duplicates (renamed variables, reordered params) — prefer the jscpd path when available, and reserve Grep for when it is not. **Duplication signals to classify** (both the jscpd and the Grep path feed the same categories in Step 2): - Utility functions defined identically in multiple files (string truncation, date formatting, validation) - Identical error handling blocks (try/catch patterns, error state JSX) - Copy-pasted UI fragments (pagination controls, confirmation dialogs, loading states) - Repeated hook/state management patterns (delete confirmation + mutation + handler) - Duplicated import blocks that signal repeated inline implementations ### Step 2: Classify duplications Group discovered duplications into extraction categories: | Category | Extract Into | Location Convention | |----------|-------------|---------------------| | **Utilities** | Pure functions | `src/lib/utils/` or `src/utils/` | | **Components** | Shared UI components | `src/components/ui/` or `src/components/shared/` | | **Hooks** | Custom React/Vue hooks | `src/hooks/` or `src/composables/` | | **Types** | Shared type definitions | `src/types/` or alongside the abstraction | Follow the project's existing conventions for shared code location. If no convention exists, propose one based on the framework. ### Step 3: Plan extractions For each duplication cluster, plan the extraction: 1. **Name the abstraction** — Use a clear, descriptive name that reflects the shared behavior 2. **Define the interface** — Determine parameters needed to cover all usage variations 3. **Choose the location** — Follow project conventions for shared code placement 4. **List all consumers** — Identify every file that will be updated 5. **Assess risk** — Note any subtle differences between duplicated instances that need parameterization Present the plan to the user before proceeding (unless `--dry-run` was not specified and the scope is clear). **Plan format:** ``` ## Extraction Plan ### 1. [Abstraction Name] → [target file path] - Type: utility | component | hook - Replaces: [N] identical blocks across [M] files - Consumers: [list of files] - Parameters: [any variations that need to be parameterized] - Duplicated: [N] tokens / [N] lines (from jscpd; blank when the Grep fallback was used) - Similarity: [N]% (from jscpd; "exact" when ast-grep-confirmed as the same shape) - Estimated lines saved: [N] ``` The `Duplicated` and `Similarity` fields come from jscpd's report (tokens/lines per clone, and the cluster's percentage) — a quantified `--dry-run` report instead of a best-effort narrative. When the Grep fallback (1c) supplied the cluster, leave them blank or note "grep-estimated". ### Step 4: Extract shared abstractions Execute each planned extraction: 1. **Create the shared abstraction** with proper typing and documentation 2. **Replace each instance** in consumer files with an import + usage of the new abstraction 3. **Handle variations** — parameterize differences between instances rather than creating multiple abstractions 4. **Update imports** — add the new import, remove imports that were only needed for the inline version **Extraction order:** Start with utilities (no dependencies), then components, then hooks (may depend on utilities/components). Mark each extraction as completed in the tracker before moving to the next. ### Step 5: Write tests Write tests for each extracted abstraction: | Abstraction Type | Test Approach | |-----------------|---------------| | Utility function | Unit tests covering all input variations, edge cases | | UI component | Render tests, prop variations, accessibility | | Custom hook | Hook testing with mock dependencies, state transitions | | Type definitions | Type-level tests if applicable (tsd, expect-type) | Place test files adjacent to the abstraction or in the project's test directory, following existing conventions. ### Step 6: Clean up dead code After all extractions are complete: 1. **Remove unused imports** from all updated consumer files 2. **Remove dead code** — inline helper functions that are now replaced 3. **Verify no orphaned references** — search for any remaining references to removed code ### Step 7: Verify all checks pass Run the full verification suite: **TypeScript/JavaScript projects:** ```bash npx tsc --noEmit # Type checking npm run lint # Linting (or biome/eslint directly) npm run test # Full test suite ``` **Python projects:** ```bash ty check . # Type checking ruff check . # Linting pytest # Test suite ``` **Rust projects:** ```bash cargo check # Type checking cargo clippy # Linting cargo test # Test suite ``` All three must pass. If any fail, fix the issues before reporting completion. ### Output Summary After all phases complete, report: ``` ## DRY Consolidation Summary ### Extractions - [Abstraction Name] (type) — replaced N blocks in M files - ... ### New Files Created - path/to/new/file.ts — [description] - ... ### Tests Added - N tests across M test files ### Net Effect - ~N lines of duplicated code consolidated - N reusable abstractions created - All verified: typecheck + lint + N passing tests ``` ## Agentic Optimizations | Context | Approach | |---------|----------| | Deterministic clone scan | `npx jscpd --reporters json --min-tokens 50 --output /tmp/jscpd-dry --silent <path>` then parse `duplicates[]` for exact ranges | | Structural shape confirm | `ast-grep -p '<pattern with $METAVARS>' --lang <lang> <path>` | | Quick scan | Use `--dry-run` to see duplication report without changes | | Focused extraction | Use `--scope utilities` to extract only utility functions | | Large codebase | Scope to specific directory: `/code:dry-consolidation src/components/` | | Post-extraction verify | `npx tsc --noEmit 2>&1 | head -30` for quick type error check | | Test run (fast) | `npm test -- --bail=1 --reporter=dot` for quick pass/fail | ## See Also - `/code:refactor` — Functional refactoring of a file or directory (pure functions, immutability, composition) - `/code:antipatterns` — Detection-only analysis for code smells - `ast-grep-search` — Structural code search for finding patterns ## Related Skills - If dead code detected during consolidation → `/code:dead-code` - If complexity is high after consolidation → `/code:complexity`