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simplify

Review recent code changes for duplication, maintainability, and wasted work, then apply straightforward improvements. The workflow combines three parallel reviews, prioritizes small, low-risk fixes, and checks the edited code with relevant tests or project checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Review recent code changes for reuse, code quality, and efficiency, then directly apply straightforward cleanup improvements. Use when the user wants a post-implementation cleanup pass, pre-PR polish, or asks to simplify/refine recent changes. Invoke with `/simplify` or `/simplify <focus>`.

설치 방법 보기

이럴 때 유용합니다

  • Cleaning up code after implementation
  • Polishing changes before opening a pull request
  • Reducing duplication in recent changes
  • Reviewing unnecessary processing and overhead

포함된 파일(1)

  • SKILL.md5.1 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Simplify Recent Changes

You are running a structured cleanup workflow over recent code changes. Your goal is not just to comment on the code, but to safely improve it.

Step 1: Identify the review scope

Determine which files and changes to review.

  1. First inspect the current git state.
  2. If there are staged changes, review against HEAD so both staged and unstaged tracked changes are included.
  3. Otherwise review the current uncommitted diff.
  4. If there is no git diff, fall back to git ls-files --modified --others --exclude-standard so the scope respects .gitignore (this keeps build output, node_modules, and other ignored paths out of the cleanup).
  5. If that is still empty, fall back to files edited in this conversation.
  6. If you still cannot identify a meaningful scope, stop and tell the user there are no recent changes to simplify.

Preferred commands:

  • git diff --name-only
  • git diff --staged --name-only
  • git diff HEAD --name-only
  • git diff
  • git diff HEAD
  • git status --short

Use git diff HEAD whenever staged changes exist. Otherwise use git diff.

Step 2: Launch three review passes in parallel

Use the agent tool and launch all review passes in a single response so they run concurrently. Set subagent_type: "general-purpose" and run_in_background: false on every call — each pass must return its findings inline. Do NOT fork them: never set subagent_type: "fork". A fork runs fire-and-forget and never returns its findings, so there would be nothing to aggregate in Step 3. Each pass must receive the same review scope and diff command. These passes are read-only: each one inspects and reports findings only and must not modify files — all edits happen later in Step 4.

Keep each review prompt short and focused. Do not paste the full diff into the prompt. Tell each pass to read the diff itself and inspect only files relevant to its findings.

Pass 1: Code Reuse Review

Look for opportunities to reduce duplication and reuse existing code:

  • existing utilities or helpers that should be reused
  • duplicated logic introduced in new code
  • inline logic that should delegate to an existing abstraction
  • ad-hoc helpers for string, path, env, parsing, or type checks when a project utility already exists

Pass 2: Code Quality Review

Look for maintainability issues:

  • copy-paste variants that should be unified
  • parameter sprawl or awkward APIs
  • redundant state or indirection
  • abstraction leaks
  • stringly-typed code that should be modeled more clearly
  • unnecessary nesting
  • unnecessary comments that explain what instead of why
  • naming or structure that does not match surrounding code

Pass 3: Efficiency Review

Look for wasteful work and unnecessary overhead:

  • repeated work that can be memoized, cached, or removed
  • serial work that can be parallelized safely
  • unnecessary scans, allocations, reads, or traversals
  • hot-path blocking work
  • redundant no-op updates
  • overly broad operations when a narrower one would work
  • existence-check patterns that introduce TOCTOU style waste or risk

Step 3: Aggregate findings

Wait for all three passes to finish, then merge overlapping findings.

Prioritize fixes that are:

  • low risk
  • local in scope
  • clearly aligned with existing project patterns
  • easy to validate with tests or targeted commands

Do not force a cleanup if it would require speculative architectural changes.

Step 4: Apply straightforward improvements

Directly implement safe cleanup improvements.

Examples of good automatic fixes:

  • replace duplicated logic with an existing helper
  • remove redundant code, but only after a repository-wide search confirms it has no remaining callers
  • simplify conditionals or control flow
  • tighten loops or repeated work
  • reduce unnecessary state or wrapper code
  • remove low-value comments
  • align code with nearby conventions

Skip items that are uncertain, risky, or too invasive. Do not spend time debating rejected findings; simply move on.

Step 5: Verify the cleanup

After making changes:

  1. Run focused tests for the changed area when they exist.
  2. Run the relevant project quality checks you can identify for the touched code.
  3. If there are no applicable tests, at least run a targeted build, typecheck, or lint command that covers the edited files.

Prefer targeted verification over whole-repo commands unless the project only exposes repo-wide checks.

Additional focus

If the user supplied extra instructions after /simplify, treat them as additional review focus and prioritize them alongside the default dimensions.

The raw user invocation appears below when present. Use it to extract any extra focus such as performance, duplication, rendering, API clarity, testability, or naming consistency.

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같은 저장소의 스킬

Write clear briefs for subagents and conversation forks, agents that inherit conversation history. Specify purpose, known findings, scope, and expected output while respecting each agent's existing role and separating research requests from implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Writing a focused research brief for a subagent
  • Specifying files and constraints for implementation
  • Defining scope for an agent inheriting conversation history
QwenLM/qwen-code2.9만2026년 10월 18일 업데이트

Compare a feature implemented in Qwen Code with Codex or Claude Code under the same scenario. Capture communication and terminal records, inspect tool definitions and outputs, and guide fixes toward matching observable behavior.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Checking a reproduced feature against its reference agent
  • Comparing tool definitions and required arguments
  • Investigating differences in terminal output
QwenLM/qwen-code2.9만2026년 10월 18일 업데이트

Reproduce a Codex or Claude Code feature in Qwen Code or another command-line agent. Capture requests, terminal output, and state changes, then use that evidence to implement focused behavior and add a verification path.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Reproduce an existing agent's slash command
  • Inspect request formats and tool definitions
  • Compare terminal output and saved state
QwenLM/qwen-code2.9만2026년 10월 18일 업데이트

autofix

무료

Review local uncommitted changes, verify findings, and repeat focused repairs until the review converges or a blocker remains. Also supports Qwen Code issue fixes and review responses within workflows run through GitHub Actions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Review and repair local uncommitted changes
  • Develop a focused fix for a selected issue
  • Verify and address pull request feedback
QwenLM/qwen-code2.9만2026년 10월 18일 업데이트

batch

무료

Apply the same operation across multiple files using parallel worker agents. The skill finds matching files, divides the work, and reports successes, failures, and skipped files, with a preview option before edits.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Add license headers across source files
  • Convert JavaScript files to TypeScript
  • Fix the same lint issue in multiple files
QwenLM/qwen-code2.9만2026년 10월 18일 업데이트

batch-api

무료

Prepare shared instructions for translating, rewriting, or extracting information from many independent files, then submit a plan through the DashScope Batch API. Processing runs asynchronously at half the realtime list price and delivers new files later.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Translate many documents using shared terminology
  • Rewrite independent files into a consistent format
  • Extract structured data from a collection of files
QwenLM/qwen-code2.9만2026년 10월 18일 업데이트

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