Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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hybridlabor-api/aos62026年10月16日 更新
免费在 GitHub 公开
codebase-memory
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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查看安装方法包含的文件（1）
- SKILL.md2.2 KB
SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
codebase-memory — indexed code knowledge graph over MCP
codebase_memory_mcp is the MCP server for the third-party
codebase-memory-mcp binary: it
indexes a repository into a persistent, local SQLite knowledge graph and answers
structural queries in-process. Everything stays on the machine — no cloud calls,
no API keys. Prerequisite: requires the codebase-memory-mcp binary on PATH. Install with:
curl -fsSL https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.sh | bash (or npm install -g codebase-memory-mcp).
If the server is absent, ask the user to install it per
docs/codebase-memory.md; do not pretend to have graph access.
Core workflow
- Index once: say "index this project" or run
codebase-memory-mcp cli index_repository '{"path": "."}'before deep dives. - Prefer graph queries over file reads when the question is structural:
get_architecture(one call for the whole repo),trace_path(call chains),search_graph(regex/label search),detect_changes(git-diff impact). Only open a file to confirm the findings you already have. - Context minimisation: one graph query replaces dozens of grep/read cycles (~99% fewer tokens). Never paste file contents to "explore"; query the graph and read only the cited file, then cite it in your answer.
Synergy with the AOS local stack
- memB: the graph holds structure, memB (
memb-mcp) holds project memory and conversation semantics — query memB for "what we decided", the graph for "how the code is wired". - Synapse: Synapse visualises the codebase spatially (
synapse map <repo>); use the graph for precise symbol-level questions and Synapse for spatial orientation, then the source files for verbatim confirmation.
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同一仓库的技能
Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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hybridlabor-api/aos62026年10月16日 更新
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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hybridlabor-api/aos62026年10月16日 更新
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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hybridlabor-api/aos62026年10月16日 更新
Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
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hybridlabor-api/aos62026年10月16日 更新
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.
中文简介正在准备中。当前显示原文说明。
hybridlabor-api/aos62026年10月16日 更新