🧪 AGI Distiller

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Knowledge Distillation System for AI Coding Agents

Read. Distill. Evolve. Repeat.

🌐 中文版 README

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🌟 Vision

AGI Distiller is not just another skill collection. It is a living knowledge distillation system that:

1. Reads high-quality technical content (articles, blogs, papers, WeChat posts)
2. Extracts pain points, solutions, and actionable rules
3. Precipitates them into cross-platform agent skills, behavioral rules, and collaboration protocols
4. Evolves itself — the more it reads, the more capable it becomes

The ultimate goal: An AI agent that continuously self-improves by reading, distilling, and applying knowledge — one article at a time.

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🔬 What Makes This Different

Dimension	Traditional Skill Repos	AGI Distiller
Source	Developer experience	High-quality technical content
Creation	Hand-written	Distilled from content
Evolution	Manual PRs	Self-evolving
Focus	General coding	Terminal AI agent efficiency
Language	English only	Bilingual (EN + CN)
Philosophy	"Here are the skills"	"Here is the distillery that produces skills"

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🏗️ System Architecture

                    ┌─────────────────────────────┐
                    │     Knowledge Sources        │
                    │  laodad.com · WeChat · Blogs │
                    │  arXiv · GitHub Issues · More │
                    └─────────────┬───────────────┘
                                  │ Read
                    ┌─────────────▼───────────────┐
                    │     Distillation Pipeline    │
                    │                              │
                    │  ① Extract Pain Points      │
                    │  ② Extract Solutions        │
                    │  ③ Derive Actionable Rules  │
                    │  ④ Precipitate into Skills  │
                    │  ⑤ Update Behavior Rules    │
                    └─────────────┬───────────────┘
                                  │ Output
        ┌─────────────────────────┼─────────────────────────┐
        ▼                         ▼                         ▼
┌───────────────┐       ┌───────────────┐       ┌───────────────┐
│  Agent Skills  │       │  Rules & Specs │       │  Memory &     │
│  (SKILL.md)    │       │  (ATOMCODE.md) │       │  Knowledge    │
│  Cross-platform│       │  Best practices│       │  (notes/)     │
└───────────────┘       └───────────────┘       └───────────────┘

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📦 What's Inside

Agent Spec Files (OpenAI Open Standard)

File	Purpose	Size
SOUL.md	Agent personality (name, character, service targets)	~1187 chars
AGENTS.md	Permission matrix + red line rules (core security)	~2320 chars
USER.md	Current user identity and role	~639 chars
TOOLS.md	Tool usage guide	~1497 chars
IDENTITY.md	Agent identity metadata	~1064 chars
HEARTBEAT.md	Session / health tracking	~825 chars
Total		~7532 chars

Skills (Cross-Platform)

Skill	Description	Status
acceptance-checker	7-item acceptance checklist for every task	✅ Live
automation-gray-release	Gray-release discipline for scheduled automations — manual trial first, verify on-disk artifact, then schedule; cost control and silent-failure guards	✅ Live
cli-safety	Agent-friendly CLI execution rules (structured output, exit code, non-interactive, idempotent, audit, file-based success)	✅ Live
code-review-p0	P0/P1/P2 graded code review with file location + cause + impact + suggestion	✅ Live
debug-flow	5-step debugging workflow (reproduce → locate → fix → test → regression), with 5-step localization method	✅ Live
dependency-verify	Dependency-change verification — installed ≠ works: a successful install or import does not prove the native library loads	✅ Live
deploy-checker	8-item pre-release checklist (scope, diff, test, UI, rollback, notes, observe, honesty)	✅ Live
doc-freshness-check	Doc-rot detection — keep README/docs in sync with code; stale-marker and terminology-change propagation	✅ Live
hook-safety-checker	Pre-flight for writing, wiring and accepting any hook (pre-commit, PreToolUse, PostToolUse, CI gate); prevents silent hooks	✅ Live
learning-accelerator	Use AI tooling to learn a new field fast — new framework, concept, interview prep, technology survey	✅ Live
long-task-resume	Resumable long-running jobs — checkpoint first, idempotent reruns, sentinel-based success, explicit recovery command	✅ Live
memory-layer-router	Five-layer memory routing decision tree — which layer (SOUL / IDENTITY / USER / MEMORY / daily log / skills) new information belongs to	✅ Live
rule-migrator	Rule-file migration and multi-tool sync (Cursor Rules / CLAUDE.md / AGENTS.md)	✅ Live
session-handoff	Session-handoff artifact — write an evidence-linked, fail-closed handoff file instead of a chat summary	✅ Live
skill-authoring-check	Skill authoring compliance baseline — frontmatter field limits (name/description/compatibility), description formula, progressive disclosure budgets, degrees of freedom, anti-patterns, pre-submit checklist	✅ Live
task-automator	Automation task writer — write repeatable, verifiable automation workflows	✅ Live
task-briefer	Structured task brief template (background, goal, scope, limits, acceptance, delivery) — probe for missing context	✅ Live
tdd-discipline	AI pair-programming TDD discipline — red/green cycle constraints, read the diff instead of trusting summaries	✅ Live
untrusted-content-boundary	Trust boundary when an agent consumes untrusted external content (webpages, issues/PRs, comments, downloads) — treat it as data not instructions, segregate and label it, least-privilege tools, human approval before high-impact actions	✅ Live
version-guard	Version management and rollback for workflows, configs and apps (Dify, n8n, CI config)	✅ Live
workspace-isolation	Multi-workspace context isolation — locate the workspace first, identify foreign files, always use explicit paths	✅ Live

Knowledge Base

• sources/ — Index of all distilled content with extraction metadata
• rules/ATOMCODE.md — Comprehensive behavioral specification (14 sections)
• DISTILLER.md — Distillation pipeline specification
• ROADMAP.md — 4-phase development roadmap

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🔧 Installation

Claude Code

/plugin marketplace add TrueFurina/AGI-Distiller
/plugin install agi-distiller@agi-distiller

✅ 实测通过：本机 Claude Code v2.1.251 跑通 claude plugin validate → marketplace add → plugin install → plugin details 全链路，Component inventory: Skills (19) 全部加载。 ⚠️ 该记录是当次运行的观测值（运行时 19 个 skill）；后续新增 skill 后未复跑安装链路——数字保持原样，不追改成新计数。 ✅ Verified end-to-end on Claude Code v2.1.251 — all 19 skills load (that run had 19 skills; the chain has not been re-run since the skill count changed).

Codex CLI

npx skills add TrueFurina/AGI-Distiller

CLI 存在（skills@1.7.0，add <owner/repo> 语法已核对）。本机无 Codex CLI，未实装验证。 CLI exists (skills@1.7.0, add <owner/repo> syntax confirmed). No Codex CLI on this machine — install not actually verified.

Manual (Any Agent)

git clone https://github.com/TrueFurina/AGI-Distiller.git
cp -r AGI-Distiller/skills/* ~/.claude/skills/

Platform Compatibility

Verified — ✅ 实测 = ran the full chain on this machine: claude plugin validate → marketplace add → plugin install → plugin details, all 19 skills loaded (Claude Code v2.1.251 — the run predates the current skill count; not re-run since). ⚠️ 未实测 / unverified = path follows that platform's public docs; no CLI available here, never actually run.

Platform	Path	Status
Claude Code	~/.claude/skills/	✅ 实测
Codex CLI	~/.codex/skills/	⚠️ 未实测
Cursor	.cursor/skills/	⚠️ 未实测
Gemini CLI	~/.gemini/skills/	⚠️ 未实测
GitHub Copilot	.github/skills/	⚠️ 未实测
OpenCode	~/.config/opencode/skills/	⚠️ 未实测
Windsurf	.windsurf/skills/	⚠️ 未实测

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🧪 The Distillation Pipeline

Every skill in this repository is born from a structured process:

1. READ  an article
2. EXTRACT:
   - Pain point: What problem does this solve?
   - Solution: How does it solve it?
   - Actionable rule: What should the agent do differently?
   - Trap: What should the agent avoid?
3. CLASSIFY: Does this fit an existing skill? Or need a new one?
4. PRECIPITATE:
   - If new rule → update ATOMCODE.md
   - If cross-session value → write to memory
   - If high-frequency pattern → create/update skill
5. VERIFY: Is the skill usable? Does it solve the original pain point?

See DISTILLER.md for the complete pipeline specification.

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🗺️ Roadmap

Phase 1: Foundation (Current)

• Core distillation pipeline design
• 21 production skills
• 14-section behavioral specification (ATOMCODE.md)
• 14 persistent memory entries
• 10 distilled source notes on disk in sources/ (laodad 4 / wechat 2 / anthropic 1 / comment-distillery 1 / owasp 1 / tencent 1)
• GitHub repository live

Phase 2: Growth (Next 30 days)

• 21 skills total
• CI pipeline (.github/workflows/golden-regression.yml)
• Marketplace registration
• Automated distillation pipeline
• Community contributions

Phase 3: Ecosystem (3 months)

• 50+ skills
• Multi-source distillation (laodad.com, WeChat, Medium, arXiv)
• Web catalog for browsing skills
• 10,000+ GitHub stars

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🤝 Contributing

We welcome contributions of all kinds:

• 📝 New sources: Suggest a high-quality article to distill
• 🔧 New skills: Submit a skill based on the distillation template
• 🌐 Translations: Help translate skills to other languages
• 🐛 Bug fixes: Improve existing skills

See CONTRIBUTING.md for guidelines.

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📚 Sources Distilled

Source	Notes on disk	Category	Status
laodad.com	4	AI programming efficiency	✅
WeChat (personal AI OS, 10x learning)	2	Learning & agent workflow	✅
卡码大模型 (Tencent)	1	CLI & Agent	✅
comment-distillery	1	Skill engineering (sibling project)	✅
More coming...			🚧

10 distilled source notes on disk (sources/**/*.md). The count above is verified against the working tree by scripts/check_doc_consistency.py.

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📄 License

MIT — use these skills in your projects, teams, and tools. Full credit to the original authors of the articles that inspired each skill.

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⭐ Star History

If this project resonates with you, give it a star ⭐ — it helps more people find this vision of self-evolving AI agents.

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"The endgame is not CLI. The endgame is every piece of software growing a set of interfaces that an Agent can call, verify, audit, and be safely confined by. CLI is just the first one ready." — 卡码大模型

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License & Usage Notice

Source-Available · All Rights Reserved

This project is source-available and all rights are reserved by the author. The code is provided for viewing and evaluation purposes only — access does not grant any right to copy, modify, redistribute, use commercially, or create derivative works. Unauthorized reuse may carry legal risk. Contact the author for explicit written permission before any other use.

本仓库为「源码可查、权利保留」项目（source-available / all-rights-reserved）。代码仅供查看与评估，未授权任何复制、再分发、修改、商用或衍生创作。擅自借用代码存在法律风险；如有需要请先联系作者获取明确书面许可。