lsp-extract-function
关于
This skill extracts a selected code block into a new named function, primarily using the language server's built-in refactoring action with a manual fallback. It validates variable capture and scope to ensure correctness after extraction. Use it when you need to refactor repetitive code into reusable functions within your IDE.
快速安装
Claude Code
推荐npx skills add blackwell-systems/agent-lsp -a claude-code/plugin add https://github.com/blackwell-systems/agent-lspgit clone https://github.com/blackwell-systems/agent-lsp.git ~/.claude/skills/lsp-extract-function在 Claude Code 中复制并粘贴此命令以安装该技能
技能文档
Requires the agent-lsp MCP server.
lsp-extract-function: Extract Code Block into a Named Function
This skill RESTRUCTURES existing code — it takes code that already exists
and moves it into a new function. This is distinct from /lsp-generate, which
creates NEW code that does not yet exist (stubs, mocks, interface implementations).
Use this skill when the code is already written; use /lsp-generate when you
need to generate code from scratch.
Invocation: User provides file_path (absolute path), start_line and
end_line (1-indexed range), and new_function_name (desired name for the
extracted function).
Prerequisites
If LSP is not yet initialized, call mcp__lsp__start_lsp with the workspace
root first. Auto-inference applies when file paths are provided, but an explicit
start is required when switching workspaces.
Step 1 — Get context (document symbols)
Call mcp__lsp__open_document to open the file, then call
mcp__lsp__list_symbols to understand the containing function and scope:
mcp__lsp__open_document({ "file_path": "<file_path>" })
mcp__lsp__list_symbols({ "file_path": "<file_path>" })
This establishes:
- Which function contains the selection
- Whether
new_function_namealready exists in the file (name collision check)
Mandatory name collision check: If new_function_name already exists as a
symbol in the document symbols list, report the conflict and stop immediately:
Cannot extract: function
new_function_namealready exists in this file. Choose a different name and retry.
Step 2 — Check server capabilities
Call mcp__lsp__get_server_capabilities to understand what the language server
supports:
mcp__lsp__get_server_capabilities({})
Check for codeActionProvider in the response. Note whether execute_command
is listed in executeCommandProvider.commands. This determines whether the
primary path (Step 3) is available.
Step 3 — Primary path: LSP code action
Call mcp__lsp__suggest_fixes with the selection range:
mcp__lsp__suggest_fixes({
"file_path": "<file_path>",
"start_line": N,
"start_column": 1,
"end_line": M,
"end_column": 999
})
Filter the returned actions for extract-function actions: include any action
whose kind contains "refactor.extract" OR whose title contains both
"Extract" and "function" (case-insensitive).
If an extract-function action is found:
- Display the action title to the user
- If the action proposes a different name than
new_function_name, ask for confirmation before proceeding - Execute via
mcp__lsp__execute_commandif the action has acommandfield:mcp__lsp__execute_command({ "command": "<action.command.command>", "arguments": <action.command.arguments> }) - OR apply directly via
mcp__lsp__apply_editif the action has aneditfield:mcp__lsp__apply_edit({ "workspace_edit": <action.edit> }) - Skip to Step 5 after applying.
If no extract-function action is found: fall through to Step 4 (manual fallback).
Step 4 — Manual fallback
When no code action is available, perform manual extraction:
a) Analyze the selection
Read the selected lines (start_line through end_line) and identify:
- Parameters: Variables used inside the selection that are declared outside (captured from outer scope — must become function parameters)
- Return values: Variables declared inside the selection that are used outside (must be returned from the extracted function)
- Early returns: Return statements inside the selection (the extracted function must wrap these)
b) Construct and confirm the proposed signature
Build the extracted function signature based on the captured variables analysis. Display the proposed signature to the user before writing:
Proposed extraction:
func new_function_name(param1 Type1, param2 Type2) (ReturnType, error) { // selected lines }Proceed with this signature? [y/n]
Wait for user confirmation before applying any edit.
c) Apply the extraction (order matters)
Apply edits sequentially — do NOT batch edits from different line regions into a
single apply_edit call:
-
First: Replace the selected lines with a call to the new function:
mcp__lsp__apply_edit({ "workspace_edit": { "changes": { "<file_path>": [{ "range": { "start": { "line": start_line-1, "character": 0 }, "end": { "line": end_line, "character": 0 } }, "newText": " result := new_function_name(args...)\n" }] } } }) -
Second: Insert the new function definition after the containing function's closing brace:
mcp__lsp__apply_edit({ "workspace_edit": { "changes": { "<file_path>": [{ "range": { "start": { "line": insert_line, "character": 0 }, "end": { "line": insert_line, "character": 0 } }, "newText": "\nfunc new_function_name(params) ReturnType {\n ...\n}\n" }] } } })
Apply call-site replacement first, then insert the new function. This order preserves line numbers during editing: replacing call site does not shift the insertion point for the new function definition.
Step 5 — Validate
After extraction via either path:
1. Check diagnostics
mcp__lsp__get_diagnostics({ "file_path": "<file_path>" })
If errors are reported, display them with the table of common causes below.
2. Common post-extraction errors
| Error type | Likely cause | Fix |
|---|---|---|
| Undefined variable | Captured var not passed as parameter | Add parameter |
| Type mismatch | Return type inferred incorrectly | Adjust return type in signature |
| Name shadows outer | New function name matches outer scope | Choose different name |
| Unused variable | Return value not captured at call site | Add variable at call site |
3. Format the document
mcp__lsp__format_document({ "file_path": "<file_path>" })
This cleans up indentation introduced by the extraction.
Output Format
After completing extraction, display:
## Extraction Summary
- File: path/to/file.go
- Extracted: lines N–M
- New function: new_function_name
- Path used: LSP code action / Manual fallback
- Post-extraction errors: 0
Follow with the Diagnostic Summary if any errors changed (format in references/patterns.md).
Language-Specific Notes
- Go: gopls may offer "Extract function" in code actions for selection ranges. Check code actions first; gopls support varies by version.
- TypeScript/JavaScript: typescript-language-server may offer "Extract to function in global scope" or "Extract to inner function" — filter for these titles in Step 3.
- Python: pylsp and pyright-langserver typically do NOT offer extract-function code actions. Manual fallback (Step 4) is required for Python files.
GitHub 仓库
相关推荐技能
qmd
开发这是一个本地搜索和索引的CLI工具,支持BM25、向量搜索和重排序功能。开发者可以用它快速索引本地文件(如Markdown文档)并进行混合搜索,特别适合代码库或文档的本地检索。它还提供MCP模式,能轻松集成到Claude开发环境中使用。
subagent-driven-development
开发该Skill用于在当前会话中执行包含独立任务的实施计划,它会为每个任务分派一个全新的子代理并在任务间进行代码审查。这种"全新子代理+任务间审查"的模式既能保障代码质量,又能实现快速迭代。适合需要在当前会话中连续执行独立任务,并希望在每个任务后都有质量把关的开发场景。
mcporter
开发mcporter Skill 让开发者能在Claude中直接管理和调用MCP服务器。它支持列出可用服务器、调用工具、处理OAuth认证以及管理服务器守护进程。开发者可以通过命令行式交互快速执行`mcporter list`查看服务器,或使用`mcporter call`直接调用工具,简化了MCP工作流程。
adk-deployment-specialist
开发这是一个用于部署和编排Google Vertex AI ADK智能体的Claude Skill,专为构建生产级多智能体系统而设计。它支持通过A2A协议进行智能体通信,提供代码执行沙箱和记忆库功能,并能处理智能体发现与任务提交。当开发者需要部署ADK智能体或编排多智能体协作时,可使用此Skill来简化Vertex AI Agent Engine的部署流程。
