Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Generate, scaffold, validate and lint Makefiles and .mk files: .PHONY targets, build automation, common mistakes. Use for any Makefile work.
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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。
One entry point for Makefile work, covering two phases: generating a new production-ready Makefile and validating or linting an existing one. Covers C/C++, Python, Go, Java and generic projects, GNU Coding Standards targets, security hardening and CI integration.
Generation is requirements-first (language, structure, targets, install layout) with validation as a mandatory final step; validation is a local-first, deterministic pipeline whose exit codes decide whether fixes are optional, recommended, or required. Pick the section below by the request: "create/generate/write a Makefile" → Generate; "validate/lint/check/review a Makefile" → Validate.
PREFIX=/usr/local), and which standard targets (all, install, clean, test, dist, help) are needed..mk file: quality, linting, hardening, security or troubleshooting before CI.bash scripts/validate_makefile.sh <makefile-path>
python3, pip3, make), GNU make syntax check (make -n --dry-run), mbake validate, mbake format --check, custom security/best-practice/optimization checks, plus optional checkmake and unmake when installed.0 = passed, 1 = passed with warnings (fix recommended, merge-policy dependent), 2 = failed — errors must be fixed and the run repeated.还没有评价。欢迎分享你的使用感受。
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Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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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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