“dead code”的搜索结果

Audit ClawJS/Clawix code hygiene without editing code, producing categorized findings, baseline status, and validation evidence.

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Use when you need code research over an indexed codebase with minimal context: structural graph queries (who calls X, call chains, architecture overview, dead code, cross-service HTTP routes) instead of file-by-file grep/read cycles. Also trigger to minimise token spend on repetitive code exploration.

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Record goals with measurable targets and deadlines, review progress against reported results, and update them as circumstances change. Keep a dated history in one file, with goal wording confirmed before it is saved.

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• Recording resolutions with targets and deadlines
• Reviewing progress toward existing goals
• Updating goals as circumstances change

Review code changes for unnecessary complexity, including unused flexibility, avoidable dependencies, and abstractions with little purpose. Receive concise findings that name what to remove, what can replace it, and how many lines could be cut.

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• Check code changes for over-engineering
• Find code replaceable with standard library features
• Identify unnecessary dependencies and abstractions

Review open employee leave cases for legal deadlines and required decisions. Identify cases needing action around leave designation, certification, or entitlement exhaustion, explain why they need attention, and summarize cases without issues briefly.

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• Reviewing leave cases each week
• Finding upcoming designation or certification deadlines
• Checking cases nearing the end of leave entitlement

Research game modding methods and tools across public websites and archived pages. Recover information from dead forum links, compare reports, and produce findings with source URLs, version details, credibility notes, and clearly identified gaps.

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• Find earlier modding work for a game
• Recover information from dead forum links
• Check reports about a tool's supported versions

Review concrete code changes for defects, compatibility problems, repository-rule violations, and unnecessary code. Produce evidence-based findings and, when explicitly requested, make minimal cleanup changes while checking that existing behavior is preserved.

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• Reviewing a pull request or commit range
• Inspecting staged and unstaged changes
• Finding debug residue and duplicate code

Review code changes with five parallel agents before committing. Each checks a separate area: code quality, simplicity, consistency, robustness, or task scope. Results identify issues, and every check must pass before the changes are considered ready.

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• Review changes before committing
• Find unnecessary abstractions and dead code
• Check consistency with surrounding code

Scans the codebase for dead code, tech debt, outdated dependencies, and code quality issues. Delegates to the Centinela (QA) agent.

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Use when Codex feels slow or bloated, when local sessions/logs/worktrees/config have grown over time, or when a user wants safe maintenance for Codex Desktop/CLI state. Provides a read-only report by default, backs up before applying changes, archives instead of deleting, normalizes Windows extended paths, prunes dead config projects, rotates large logs, and moves stale worktrees.

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Review AI-authored code for its characteristic failure modes — plausible-but-wrong logic, hallucinated APIs, over-engineering, dead scaffolding, and silent security shortcuts. Use when reviewing an AI-generated or heavily AI-assisted PR, when AI-written code keeps shipping subtle bugs, or when setting review standards for a team using coding agents. Produces a focused review with AI-specific findings, verification steps per risk class, and a team checklist for AI-authored changes. For general PR review use code-review-checklist — this skill covers what that one assumes a human wouldn't do.

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Edit, trim, cut, caption, subtitle, reframe, combine, add background music to, or export video, audio, and image files through Cassette. Use this skill whenever the user asks to change, preview, or render a media file in the project — even if they never say "Cassette" or name a tool — for example "trim the intro off demo.mp4", "add subtitles to this clip", "make me a 30-second cut with music", "why is there dead air at the start". Drives the local Oh My Cassette stdio MCP tools in Codex or Claude as one multi-turn conversation with the Cassette agent, with per-turn timeline previews, guided questions, and rendering only on explicit export.

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Simplify code, plans and systems without losing required outcomes; delete machinery that earns nothing; for code, AST-measured complexity with regression gates. Triggers: simplify, refactor, complexity, overengineered, dead code, useless guard.

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Use after every code change, after writing tests, or before marking a task complete, and when the user says verify, quality gate, or audit code. Runs a 7-category mechanical check for TDZ, import, dead code, and mock leakage bugs.

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Review Java concurrency code for thread safety, race conditions, deadlocks, and modern patterns (Virtual Threads, CompletableFuture, @Async). Use when user asks "check thread safety", "concurrency review", "async code review", or when reviewing multi-threaded code.

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Security scan, dead code detection, and code quality audit for any project

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Integrate ManagedCode.Orleans.Graph into an Orleans-based .NET application for grain-call policy enforcement, deadlock detection, live-call telemetry, and Mermaid graph diagnostics. USE FOR: ManagedCode.Orleans.Graph integration; allowed grain transitions; Orleans call filters; live policy graphs; reviewing Orleans call-cycle risk. DO NOT USE FOR: generic graph data modeling or traversal unrelated to Orleans calls. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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Create and maintain one committed per-project memory file (PROJECT.md) so agents stop re-discovering the same facts every cold session. Stores only the stable, expensive-to-rediscover, not-in-the-code context — architecture + why, build/test/run commands, decisions and dead-ends — as human-readable markdown, versioned with the code so it can't silently rot. Use when asked to set up project memory/context, stop agents re-grepping the codebase, scaffold or refresh a PROJECT.md / CLAUDE.md memory section, or cut cold-start rediscovery cost. Prose context only — never code, config, or data.

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Fix PostgreSQL deadlock errors caused by concurrent schema initialization in worker processes. Use when: (1) psycopg2.errors.DeadlockDetected during CREATE INDEX/TABLE IF NOT EXISTS, (2) Multiple Cloud Run jobs, Kubernetes pods, or worker processes start simultaneously, (3) Error shows "Process X waits for RowExclusiveLock... blocked by process Y", (4) init_schema() or migration code runs at worker startup. The key insight: "IF NOT EXISTS" is NOT truly concurrent-safe - PostgreSQL still acquires locks that can deadlock.

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Keeping codebases healthy, performant, and maintainable - refactoring, performance optimization, and technical debt managementUse when "refactor, optimize, performance, technical debt, cleanup, architecture, speed up, bundle size, memory leak, slow query, code smell, complexity, dead code, performance, refactoring, optimization, technical-debt, architecture, cleanup, bundle, memory" mentioned.

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Find, rank, and safely remove accidental codebase complexity by proving real consumers, dynamic entrypoints, compatibility obligations, duplicate representations, speculative surfaces, and lifecycle ownership. Use when asked to simplify or clean up a repository, reclaim code entropy, reduce over-engineering or redundancy, find deletion candidates, collapse duplicate state/APIs, remove dead or added-then-abandoned code beyond static-tool output, or implement an evidence-backed simplification pass in any language or stack. Also trigger for 代码化简、熵回收、删代码、清理冗余、收敛抽象、去除过度设计. Do not use as a performance audit unless simplification is the stated goal.

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Detects common LLM coding agent artifacts across four categories (tests, dead code, abstraction, style) over the project or changed files — using parallel subagents when the agent supports them, otherwise four sequential passes. Scans files changed since main by default; use --all for full-project scan. Triggers on LLM cruft cleanup, agent-generated code review, dead code sweeps, test-quality passes, or when the user asks to scan the whole repo.

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Review touched code for maintainability smells such as duplication, awkward indirection, suspicious clones, dead code, poor naming, and Boy Scout cleanup opportunities. Use when a broad review needs a dedicated maintainability pass or when the user asks for code-smell review specifically.

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Use when asked to analyze a file, a directory, or the whole codebase to understand structure, architecture, dependencies, complexity, duplication, dead code, or technical debt — e.g. "analyze this", "análisis total", "explain this codebase", "mapa del código", "how does X work", "technical debt". Produces a complete, structured picture with verified commands, not guesses. Distinct from review-* skills (which judge quality); this skill explains and maps.

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