Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Review a diff for clarity and safe simplifications, then optionally apply low-risk fixes.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Review changed code for reuse, quality, efficiency, and clarity issues. Use Codex sub-agents to review in parallel, then optionally apply only high-confidence, behavior-preserving fixes.
Choose the mode from the user's request:
review-only: user asks to review, audit, or check the changessafe-fixes: user asks to simplify, clean up, or refactor the changesfix-and-validate: same as safe-fixes, but also run the smallest relevant validation after editsIf the user does not specify, default to:
review-only for "review", "audit", or "check"safe-fixes for "simplify", "clean up", or "refactor"Prefer this scope order:
If there is no clear scope, stop and say so briefly.
When using git changes, determine the smallest correct diff command based on the repo state:
git diffgit diff --cachedDo not assume git diff HEAD is the right default when a smaller diff is available.
Before reviewing standards or applying fixes, read the repo's local instruction files and relevant project docs for the touched area. Prefer the closest applicable guidance, such as:
AGENTS.mdUse those instructions to distinguish real issues from intentional local patterns.
Use Codex sub-agents when the scope is large enough for parallel review to help. For a tiny diff or one very small file, it is acceptable to review locally instead.
When spawning sub-agents:
Use four review roles.
Review the changes for reuse opportunities:
Recommended sub-agent role: explorer for broad codebase lookup, or reviewer if a stronger review pass is more useful than wide search.
Review the same changes for code quality issues:
Recommended sub-agent role: reviewer
Review the same changes for efficiency issues:
Recommended sub-agent role: reviewer
Review the same changes for clarity, local standards, and balance:
Recommended sub-agent role: reviewer
Only report issues that materially improve maintainability, correctness, or cost. Do not churn code just to make it look different.
Wait for all review sub-agents to complete, then merge their findings.
Normalize findings into this shape:
Discard weak, duplicative, or instruction-conflicting findings before editing.
In review-only mode, stop after reporting findings.
In safe-fixes or fix-and-validate mode:
Prefer fixes like:
Do not stage, commit, or push changes as part of this skill.
In fix-and-validate mode, run the smallest relevant validation for the touched scope after edits.
Examples:
Prefer fast, scoped validation over full-suite runs unless the change breadth justifies more.
If validation is skipped because the user asked not to run it, say so explicitly.
Close with a brief result:
If the code is already clean for this rubric, say that directly instead of manufacturing edits.
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Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
中文简介正在准备中。当前显示原文说明。
Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.
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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
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agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
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