// Use when auditing a codebase for semantic duplication - functions that do the same thing but have different names or implementations. Especially useful for LLM-generated codebases where new functions are often created rather than reusing existing ones.
Create, manage, or connect to a headless Windows 11 VM running in Docker with SSH access. Use when the user wants to spin up, stop, restart, or SSH into a Windows VM.
Use when asked to send or read Slack messages, check Slack channels, test Slack integrations, or interact with a Slack workspace from the command line.
Use MCP servers on-demand via the mcp CLI tool - discover tools, resources, and prompts without polluting context with pre-loaded MCP integrations
Use when you need to run interactive CLI tools (vim, git rebase -i, Python REPL, etc.) that require real-time input/output - provides tmux-based approach for controlling interactive sessions through detached sessions and send-keys
| name | finding-duplicate-functions |
| description | Use when auditing a codebase for semantic duplication - functions that do the same thing but have different names or implementations. Especially useful for LLM-generated codebases where new functions are often created rather than reusing existing ones. |
LLM-generated codebases accumulate semantic duplicates: functions that serve the same purpose but were implemented independently. Classical copy-paste detectors (jscpd) find syntactic duplicates but miss "same intent, different implementation."
This skill uses a two-phase approach: classical extraction followed by LLM-powered intent clustering.
| Phase | Tool | Model | Output |
|---|---|---|---|
| 1. Extract | scripts/extract-functions.sh | - | catalog.json |
| 2. Categorize | scripts/categorize-prompt.md | haiku | categorized.json |
| 3. Split | scripts/prepare-category-analysis.sh | - | categories/*.json |
| 4. Detect | scripts/find-duplicates-prompt.md | opus | duplicates/*.json |
| 5. Report | scripts/generate-report.sh | - | report.md |
digraph duplicate_detection {
rankdir=TB;
node [shape=box];
extract [label="1. Extract function catalog\n./scripts/extract-functions.sh"];
categorize [label="2. Categorize by domain\n(haiku subagent)"];
split [label="3. Split into categories\n./scripts/prepare-category-analysis.sh"];
detect [label="4. Find duplicates per category\n(opus subagent per category)"];
report [label="5. Generate report\n./scripts/generate-report.sh"];
review [label="6. Human review & consolidate"];
extract -> categorize -> split -> detect -> report -> review;
}
./scripts/extract-functions.sh src/ -o catalog.json
Options:
-o FILE: Output file (default: stdout)-c N: Lines of context to capture (default: 15)-t GLOB: File types (default: *.ts,*.tsx,*.js,*.jsx)--include-tests: Include test files (excluded by default)Test files (*.test.*, *.spec.*, __tests__/**) are excluded by default since test utilities are less likely to be consolidation candidates.
Dispatch a haiku subagent using the prompt in scripts/categorize-prompt.md.
Insert the contents of catalog.json where indicated in the prompt template. Save output as categorized.json.
./scripts/prepare-category-analysis.sh categorized.json ./categories
Creates one JSON file per category. Only categories with 3+ functions are worth analyzing.
For each category file in ./categories/, dispatch an opus subagent using the prompt in scripts/find-duplicates-prompt.md.
Save each output as ./duplicates/{category}.json.
./scripts/generate-report.sh ./duplicates ./duplicates-report.md
Produces a prioritized markdown report grouped by confidence level.
Review the report. For HIGH confidence duplicates:
Focus extraction on these areas first - they accumulate duplicates fastest:
| Zone | Common Duplicates |
|---|---|
utils/, helpers/, lib/ | General utilities reimplemented |
| Validation code | Same checks written multiple ways |
| Error formatting | Error-to-string conversions |
| Path manipulation | Joining, resolving, normalizing paths |
| String formatting | Case conversion, truncation, escaping |
| Date formatting | Same formats implemented repeatedly |
| API response shaping | Similar transformations for different endpoints |
Extracting too much: Focus on exported functions and public methods. Internal helpers are less likely to be duplicated across files.
Skipping the categorization step: Going straight to duplicate detection on the full catalog produces noise. Categories focus the comparison.
Using haiku for duplicate detection: Haiku is cost-effective for categorization but misses subtle semantic duplicates. Use Opus for the actual duplicate analysis.
Consolidating without tests: Before deleting duplicates, ensure the survivor has tests covering all use cases of the deleted functions.