开发技能

Create a reusable command with explicit preconditions, numbered actions, checks after each step, and error handling. This template provides a structure to customize so Claude verifies the required context before starting a defined workflow.

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• Turning a recurring task into a reusable command
• Defining checks for files, permissions, and configuration before work
• Adding validation after each workflow step

Read staged Git changes and suggest a message in Conventional Commits format, a structured way to describe changes. Include a concise subject and relevant details, then request confirmation before creating the commit.

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• Draft a message for staged changes
• Use a consistent commit message format
• Document the purpose of a change

Explain code, design concepts, and system behavior at a chosen level of detail. Get a brief overview or a deeper walkthrough covering execution flow, design choices, alternatives, usage examples, and related code.

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• Understanding an unfamiliar file or function
• Tracing authentication or data flow
• Comparing design choices and alternatives

Organize open pull requests by size, automated check results, inactivity, and overlapping files. Review selected changes in depth, prepare comments for approval, and optionally create separate local working directories for hands-on review.

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• Prioritize a backlog of open pull requests
• Find overlapping changes and failing automated checks
• Draft and approve review comments before posting

Troubleshoot Claude Code problems by comparing reported symptoms with configuration scans and a troubleshooting guide. It asks follow-up questions when needed and proposes targeted fixes for permission prompts, tool connections, hooks, installation errors, and performance issues.

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• Investigating repeated permission prompts
• Diagnosing MCP server connection failures
• Checking why settings or hooks are ignored

Audit Claude Code instruction rules against actual project files to find broken settings, overly broad scopes, and loading issues. Review each rule’s usefulness with the user, then apply confirmed changes or produce an audit report.

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• Setting up Claude Code rules for the first time
• Investigating rules that apply too often or never
• Reviewing outdated instructions

Trace how AI tooling developed in a Git repository by identifying configuration file origins, monthly commit activity, major changes, and relevant releases. Produce a Markdown report that explains adoption phases and turning points using Git evidence.

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• Finding when AI configuration files were first introduced
• Reviewing monthly activity around AI tooling changes
• Tracing major integrations and workflow changes

Audit a collection of agent skills for valid settings, clear activation conditions, complete workflows, and required files. Get scores for each target platform, prioritized fixes, and a separate record of whether activation was actually tested.

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• Checking skill quality before publication
• Reviewing an imported skill collection
• Investigating excessive or missing automatic activation

Rebuild project context after clearing a conversation or returning to work. Review recent Git history, uncommitted changes, and TODO markers to get a structured summary of project status and suggested next steps.

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• Restoring project context after /clear
• Reviewing recent changes after a long break
• Checking unfinished work before choosing the next task

Measure code patterns such as casts to any or disabled lint rules, then run repeated, targeted edits. Keep changes that improve the chosen metric, revert unsuccessful changes, and track results for each improvement loop.

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• Finding code patterns to prioritize for cleanup
• Preparing measurement files for an improvement loop
• Repeating targeted edits to reduce casts to any

Examines project code, development history, tests, and documentation, then asks three focused questions to recommend a combination of AI-assisted development methods, with practical starting steps tailored to the project.

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• Choosing development methods for a solo prototype
• Reviewing workflows for an existing SaaS product
• Selecting evaluation methods for an AI product

Analyze changed files and commits before opening a pull request, a proposed code change for review. Identify oversized or unrelated changes, suggest splits, and create a GitHub PR with a summary, description, and checklist.

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• Prepare a pull request for review
• Check whether large changes should be split
• Create a draft PR with labels

Remove a specific Git worktree, a separate working directory for a branch, after checking uncommitted work and merge status. Clean up branches and stale references, protect important branches, and provide reminders for related database cleanup.

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• Remove a worktree after finishing a task
• Check for unmerged or uncommitted work before removal
• Remove a worktree while keeping its branch

Analyze TypeScript and JavaScript code for reusable design structures known as GoF patterns. Get detection reports, quality scores, and prioritized refactoring suggestions that account for the frameworks and libraries already used in the project.

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• Find existing design patterns in a codebase
• Plan refactoring for complex conditionals
• Evaluate the quality of a pattern implementation

Build an MCP integration skill using a template that reads server-specific reference notes before calling tools. The Sentry example gathers unresolved errors, groups them by likely root cause, and produces a report with investigation suggestions.

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• Design a skill that integrates with an MCP server
• Document server-specific query pitfalls
• Group Sentry errors by likely root cause

Analyze code, database queries, or systems for performance problems involving speed, memory, and frontend file size. Get prioritized recommendations with code examples, expected impact, implementation effort, risks, and a roadmap for improvements.

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• Investigate a slow function or module
• Review memory usage and possible leaks
• Find inefficient database queries

Investigate bugs by tracing symptoms through code and recent changes, reproducing failures, and testing a specific cause before fixing it. Produce a focused correction, a regression test to catch recurrence, and an evidence-based debugging report.

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• Investigate errors that keep returning after fixes
• Trace a regression through recent changes
• Analyze failures that occur only in certain environments

Analyze files or modules for duplicated code, excessive complexity, and violations of SOLID, five software design principles. Get prioritized refactoring suggestions with affected locations, risks, estimated effort, and testing needs to guide code improvements.

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• Reviewing responsibilities in oversized files and classes
• Finding duplicated code and deeply nested logic
• Prioritizing refactoring by impact, risk, and effort

Clean up Git worktrees, separate working folders for branches, by identifying merged branches and reviewing unmerged ones. Preview deletions, preserve protected branches, and receive a report of removed folders and reclaimed disk space.

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• Clean up worktrees after merging branches
• Preview deletions and potential disk savings
• Review unmerged worktrees individually

Polish Korean commit messages drafted by AI into natural developer language. The skill removes stiff wording and literal translations while preserving the stated changes, commit type, scope, issue numbers, and code identifiers.

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• Polishing Korean commit message drafts
• Keeping Conventional Commits prefixes intact
• Reviewing several commit messages together

Review Apache Pinot changes affecting frequently executed code or making performance claims in a pull request. Relevant areas include operators, segment readers, aggregation functions, and locking inside loops that process individual rows.

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• Review changes to frequently executed processing code
• Review performance improvement claims in a pull request
• Review locking inside per-row loops

Review Apache Pinot changes against naming and API conventions, including public names, method signatures, REST endpoints, JSON fields, and documentation. Use it when adding or renaming elements exposed to other code or users.

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• Reviewing public class, method, or field names
• Checking new enum constants or DataType values
• Reviewing REST endpoints and JSON fields

Review Apache Pinot changes for concurrency and state safety, including locks, shared callbacks, lifecycle changes, and distributed metadata. Use it to examine how changes affect shared state when multiple operations run at the same time.

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• Reviewing changes to locks and atomic operations
• Checking shared callback registration changes
• Reviewing Helix state transitions and ZK node changes

Start a local Pinot quickstart and verify it using modes supported by the checked-out code. Use it to bring up a local trial environment that matches the version you are working with.

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• Start a local Pinot quickstart
• Use a mode supported by the checked-out code
• Verify the quickstart after startup