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mokhtarabadi/cognitive-lead-hq

mokhtarabadi/cognitive-lead-hq

The centralized Headquarters for the Cognitive Lead AI multi-agent system. Features hallucination-resistant system prompts, MCP servers, and strict Agent Skills.
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8 ★ · mokhtarabadi/cognitive-lead-hq · 取自 GitHub 搜索 API · (2026-10-16 20:00:20 核对)
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从该仓库的 GitHub 页面直接读取 · 条目类型:开源项目
收录与活跃
收录于 2026-10-13 · 最近见到 2026-10-13 · 共见到 1 次 · 被 1 个来源列出
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综合分 103 · 8 ★ · 1 个来源 · repo
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: Agent 技能、AI Agent。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 mokhtarabadi/cognitive-lead-hq;我们收录于 2026-10-13;最近见到 2026-10-13。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

Cognitive Lead AI HQ 🧠⚡

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

Autonomous Multi-Agent Orchestration Platform • Industrial 9-Step Production Line • FastMCP Tooling for OpenCode & Claude
The centralized **Headquarters** for the Cognitive Lead AI multi-agent system — a collection of hallucination-resistant system prompts, MCP servers, and strict Agent Skills (SKILL.md) built for OpenCode.
> **Quick Install:** Copy this line and give it to OpenCode:
>
>
---
🚀 Quick Start
Give the prompt above to OpenCode and it will auto-configure itself globally using LLM.txt — the canonical auto-setup source. No manual steps required.
For full platform-specific instructions (Windows, macOS, Linux), see LLM.txt.
See docs/setup.md for full setup instructions and all platform tools.
---
🧠 How to Operate: The Brain & 🛠️ The Hands
This system relies on a strict separation of concerns:
- **The Brain (The Orchestrator):** Lives behind the brain_turn MCP tool. It has _no_ direct access to your files or terminal. It thinks, plans, and returns XML task blocks or verdict reports.
- **The Hands (OpenCode):** Runs locally on your machine. It calls the Brain itself, executes file changes, runs bash commands, triggers Agent Skills, and records results in the task file. You never ferry text between them.
- **The QA Loop:** After implementation, the Hands sends the task file to the Brain for QA and review through the same tool. If QA fails, a fix round runs. If QA passes, the task moves to tasks/qa/ and waits for your approval word before it is committed and closed.
Scenario A: Phase 0 for a Brand New Project
1. Initialize an empty repository on your machine and start OpenCode.
2. In the Orchestrator, paste the system-prompt.md and say: _"This is a new project. Start Phase 0."_
3. Tell the AI your desired tech stack (e.g., Next.js, Node.js).
4. The AI will generate an implementation task instructing OpenCode to:
- Copy the relevant stack SKILL.md template from your global skills directory.
- Create opencode.json with the required schema.
- Set up the tasks/ directory and use the task-generator skill to create your first 01-initial-setup.md task.
Scenario B: Phase 0 for an Existing Project (Never used this workflow)
1. Open your existing project in OpenCode.
2. In the Orchestrator, paste the system-prompt.md and say: _"This is an existing project. Start Phase 0."_
3. The AI will immediately output a . Paste this into your local agent (OpenCode).
4. OpenCode will use its MCP tools to map the directory tree and read core files into a context-reports/ markdown file.
5. Copy the contents of that report and paste it back into the Orchestrator.
6. The AI will analyze your existing architecture and design, then generate an implementation task to create AGENTS.md ( 📝 **MANAGER REVIEW:** blockquotes immediately below the section you want to change.
3. Alternatively, use standard Markdown strikethrough (~~text~~) and bold (**text**) for direct edits.
4. Paste the annotated Markdown back to the Orchestrator.
The AI will process your inline feedback, generate a revised plan, and wait for your final "Approved" signal before writing code.
⚡ Manual Mode Workflow (Pure-MCP Human-in-the-Loop) — ACTIVE / DEFAULT
> **Brain Bridge active:** QA/review run through one MCP (brain_turn) — no manual ferrying, no per-persona commands. This manual cycle remains available; autopilot mode runs it end-to-end.
This is the canonical pure-MCP cycle:
1. **Manager inputs raw thought / Telegram message** — raw bilingual draft or structured task file in tasks/backlog/.
2. **Orchestrator issues architectural blueprint & awaits approval** — Brain reviews context, proposes plan, and halts for explicit Manager Approved.
3. **Hands receives the implementation XML and runs locally with ZAC enforcement** — no pasting between chats; the Hands calls the Brain itself.
4. **Hands executes code, runs tests, and invokes custom_context_qa_transition** — stages modified_files, injects factual diff, and moves task tasks/in-progress/ → tasks/qa/ via pure MCP.
5. **Hands sends the QA task file to the Brain for QA Engineer adversarial testing and Code Reviewer architectural review via brain_turn** — no pasting; history continues under the active session thread.
6. **Manager approves closure and Hands commits atomically via custom_context_commit_and_clean_task** — commits staged diff, replaces raw diff with hash reference, and moves task to tasks/completed/ — the only commit path.
来源
github · https://github.com/mokhtarabadi/cognitive-lead-hq
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