菜单
Review code for performance: complexity, database/query efficiency, I/O and network cost, memory and allocation behavior, concurrency contention, caching, and latency/throughput regressions. Cognitive-only atomic skill; output is a findings list.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | review-performance |
| description | Review code for performance: complexity, database/query efficiency, I/O and network cost, memory and allocation behavior, concurrency contention, caching, and latency/throughput regressions. Cognitive-only atomic skill; output is a findings list. |
| description_zh | 审查性能：复杂度、数据库/查询效率、I/O 与网络成本、内存与分配、并发竞争、缓存与延迟/吞吐回归。 |
| tags | ["code-review","cognitive","optimization"] |
| version | 1.0.0 |
| license | MIT |
| recommended_scope | project |
| metadata | {"author":"ai-cortex"} |
| triggers | ["review performance","performance review"] |
| input_schema | {"type":"code-scope","description":"Source files or directories to review"} |
| output_schema | {"type":"findings-list","description":"Zero or more findings with location, category, severity, and suggestion"} |
仅审查 性能 问题的代码。不要定义范围（差异与代码库）或执行安全/架构/语言框架约定分析；这些由其他原子技能处理。以标准格式发出结果列表以进行聚合。重点关注算法复杂性、查询效率、I/O 和网络成本、内存行为、争用和并发瓶颈、缓存策略以及可测量的回归风险。
首要目标：生成一个以性能为中心的结果列表，涵盖给定代码范围的复杂性热点、查询效率、I/O 成本、内存行为、并发争用、缓存和回归风险。
成功标准（必须满足所有要求）：
验收测试：输出是否包含涵盖所有相关维度的性能结果列表，以及基于证据的严重性评级和可操作的、位置参考的建议？
本技能负责：
本技能不负责：
review-dotnet、review-java、review-go 等。review-sql转交点：当所有性能结果发布后，移交给“审查代码”编排器进行聚合，或直接交付给用户进行以性能为中心的审查会议。
何时使用：当任务包含绩效审核时。范围和代码范围由调用者或用户确定。
不要做这些（其他技能可以处理它们）：
review-sql何时停止并交接：
输出是否包含涵盖所有相关维度的绩效结果列表，以及基于证据的严重性评级和可操作的、位置参考的建议？
Store, look up, or delete a personal credential (server SSH password, database password, website login, API key/token, certificate passphrase) in the macOS Keychain using a consistent <project>-<env>-<kind> naming scheme, and optionally record a pointer (never the secret itself) in the current project's Claude Code memory. Always use this skill whenever the user asks to save, store, remember, look up, rotate, or delete a password, API key, token, SSH credential, or database credential on this machine — even if they don't say "Keychain" or "security" explicitly, e.g. "save this database password so I don't lose it", "把这个数据库密码存一下", "记一条密钥", "这台服务器的密码帮我记下来", "what's the postgres password for staging again", "delete the old GitHub token from keychain". Do not use this for team-shared secret vaults, CI/CD secret injection, or anything that needs to sync across machines — those need a real secrets manager, not this skill.
Drain pending NATS messages from a producer contract via NATS MCP tools. Discovers the available NATS tool capabilities, selects exact-subject or wildcard mode from .cortex/nats.yaml, applies Tolerant Reader semantics, executes ack/nak/term decisions, and returns aggregated stats.
Audit and refactor existing SKILLs to meet spec compliance, repository asset boundaries, tool adaptation requirements, and LLM best practices.
From inside a linked worktree, deliver the current feature branch into main — merge with --no-ff, push, and optionally clean up the worktree, all without leaving CWD.
After code changes, auto-detect the project's build system and local deployment method for a given directory, then build the project and restart its locally-deployed environment (Docker Compose / systemd / process manager). Never assumes — asks only when detection is ambiguous. Caches detected commands per project in .cortex/redeploy-local.yaml; re-invocations on the same project skip re-scanning until signal files change, the cache expires (30 days), or the skill version bumps.
From the main repo on the main branch, scan all linked worktrees and local branches, let the user multi-select, then merge --no-ff + push them sequentially and clean up succeeded worktrees together.