关于
This skill identifies semantically duplicate functions in codebases that perform the same task but have different names or implementations, which is common in LLM-generated code. It uses a two-phase approach combining classical extraction with LLM-powered intent clustering to find duplicates that syntactic tools miss. Developers should use it when auditing or refactoring a codebase to find opportunities for consolidating utility functions.
快速安装
Claude Code
推荐npx skills add obra/superpowers-lab -a claude-code/plugin add https://github.com/obra/superpowers-labgit clone https://github.com/obra/superpowers-lab.git ~/.claude/skills/finding-duplicate-functions在 Claude Code 中复制并粘贴此命令以安装该技能
技能文档
Finding Duplicate-Intent Functions
Overview
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.
When to Use
- Codebase has grown organically with multiple contributors (human or LLM)
- You suspect utility functions have been reimplemented multiple times
- Before major refactoring to identify consolidation opportunities
- After jscpd has been run and syntactic duplicates are already handled
Quick Reference
| 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 |
Process
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;
}
Phase 1: Extract Function Catalog
./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.
Phase 2: Categorize by Domain
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.
Phase 3: Split into Categories
./scripts/prepare-category-analysis.sh categorized.json ./categories
Creates one JSON file per category. Only categories with 3+ functions are worth analyzing.
Phase 4: Find Duplicates (Per Category)
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.
Phase 5: Generate Report
./scripts/generate-report.sh ./duplicates ./duplicates-report.md
Produces a prioritized markdown report grouped by confidence level.
Phase 6: Human Review
Review the report. For HIGH confidence duplicates:
- Verify the recommended survivor has tests
- Update callers to use the survivor
- Delete the duplicates
- Run tests
High-Risk Duplicate Zones
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 |
Common Mistakes
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.
GitHub 仓库
常见问题
什么是 finding-duplicate-functions Skill?
finding-duplicate-functions 是一个 Claude Skill,作者为 obra。Skill 将 Claude 按需加载的说明和资源打包,让 Claude 无需额外提示即可执行与 finding-duplicate-functions 相关的任务。
如何安装 finding-duplicate-functions?
使用本页的安装命令:将 finding-duplicate-functions 作为插件添加到 Claude Code,或将其仓库克隆到 skills 目录,然后重启 Claude 以加载该 Skill。
finding-duplicate-functions 属于哪个分类?
finding-duplicate-functions 属于元分类。
finding-duplicate-functions 可以免费使用吗?
可以。finding-duplicate-functions 已收录在 AIMCP,可免费安装。
相关推荐技能
Content Collections 是一个 TypeScript 优先的构建工具,可将本地 Markdown/MDX 文件转换为类型安全的数据集合。它专为构建博客、文档站和内容密集型 Vite+React 应用而设计,提供基于 Zod 的自动模式验证。该工具涵盖从 Vite 插件配置、MDX 编译到生产环境部署的完整工作流。
这个Claude Skill为开发者提供完整的Polymarket预测市场开发支持,涵盖API调用、交易执行和市场数据分析。关键特性包括实时WebSocket数据流,可监控实时交易、订单和市场动态。开发者可用它构建预测市场应用、实施交易策略并集成实时市场预测功能。
该Skill帮助开发者创建OpenCode插件,用于接入命令、文件、LSP等25+种事件。它提供了插件结构、事件API规范和JavaScript/TypeScript实现模式,适合需要拦截操作、扩展功能或自定义事件处理的场景。开发者可通过它快速构建响应式模块来增强OpenCode AI助手的能力。
SGLang是一个专为LLM设计的高性能推理框架,特别适用于需要结构化输出的场景。它通过RadixAttention前缀缓存技术,在处理JSON、正则表达式、工具调用等具有重复前缀的复杂工作流时,能实现极速生成。如果你正在构建智能体或多轮对话系统,并追求远超vLLM的推理性能,SGLang是理想选择。
