Agent Commons

A protocol that lets any sufficiently intelligent AI agent join your shared memory by simply reading one file.

English | 中文

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You probably switch between multiple AI agents every day — Claude Code, Cursor, CodeBuddy, WorkBuddy, OpenClaw, Aider, GitHub Copilot Chat… and every one of them is an isolated island. Each one has its own memory of you, none of them know what the other learned. You teach the same preferences over and over.

Agent Commons fixes that. It's a tiny protocol — not a framework, not a service, not even a library — that lets multiple AI agents on your machine share a single source of truth via plain Markdown files and Unix symlinks.

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The 30-second pitch

~/.agent-commons/                ← One central directory on your machine
│
│  ─── Protocol layer (mandatory) ───
├── ONBOARDING.md                ← One-time joining flow for new agents
├── CONVENTIONS.md               ← Optional, non-normative conventions
├── identity/                    ← Who you are (profile, routine)
├── rules/                       ← Hard rules every agent must obey
├── toolchain/                   ← Tools, paths, configs
├── projects/                    ← What you're working on
├── log/daily/                   ← Per-agent daily logs (no write conflicts)
├── handoff/                     ← Cross-agent inbox + shared state
├── skills/agent-commons/        ← Runtime skill of the protocol itself
├── registry.json                ← Which agents have joined
│
│  ─── Convention layer (optional, recommended) ───
├── skills_data/<skill>/         ← Per-skill persistent data (one backup root for all)
├── mcp/<server>/                ← Shared MCP server configs
├── plugins/<name>/              ← Shared plugins
└── tools/<name>/                ← Shared CLI scripts/utilities

Every joined agent has a symlink:

~/.<your-agent>/skills/agent-commons → ~/.agent-commons/skills/agent-commons/

That's it. No daemon. No server. No npm install. No third-party runtime. Pure filesystem.

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Why this exists (and why it's different)

Existing solution	What it does	The catch
ChatGPT Memory	Auto-remembers facts about you	Locked inside OpenAI
Claude Projects	Project-scoped context	Anthropic only
MemGPT / Letta	Long-term memory inside one agent	Doesn't span agents
Mem0	Cross-agent memory service	Needs server, REST API, vendor lock
MCP	Tool/resource protocol	Not about memory
Agent Commons	Cross-vendor, local-first, plaintext, zero-deps	Requires the agent to be smart enough to read a file

The differentiator: we don't write adapters for each agent. We write a single SKILL.md that any sufficiently intelligent LLM can read and self-onboard from. Agents that can't follow plain English instructions… don't get to join. That's the design.

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How a user makes any AI agent join

Tell the agent, in any language, any phrasing:

"Read ~/.agent-commons/ONBOARDING.md and join the Agent Commons system."

That's the entire user-side workflow. No CLI to install, no configs to edit. The agent reads the file, follows the joining flow inside, and reports back.

If the agent can't figure it out, the agent isn't smart enough for your workflow — and you'll know that, too. It's a built-in capability test.

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What the protocol actually requires of a joined agent

The protocol cleanly separates one-time joining from ongoing capabilities:

• ONBOARDING.md (one-time): discover your runtime's user-extensible skills directory, install the skill (symlink → copy → readonly fallback), run a closed-loop trigger test to prove the runtime can actually invoke it, register in registry.json.
• skills/agent-commons/SKILL.md (recurring): read shared identity / rules / current focus; check inbox / send messages; append daily logs; refresh last_seen. This is the runtime capability the joined agent carries forward.

See ONBOARDING.md for the joining flow. See skills/agent-commons/SKILL.md for the runtime capability spec. See SPEC.md for the full normative specification. See CONVENTIONS.md for optional, non-normative conventions (e.g. recommended skill data location at ~/.agent-commons/skills_data/). See skills/agent-commons/manifest.json for the machine-readable spec.

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Single source of truth — automatic protocol updates

Each joined agent's ~/.<agent>/skills/agent-commons/ is a symlink back to the central ~/.agent-commons/skills/agent-commons/. When this project ships a protocol update, you update the central dir; every agent on the user's machine sees the new version on its next session start. No push notifications, no version checks, no hash comparison. Just filesystem semantics doing what filesystem semantics do.

User-owned files (identity/, rules/, toolchain/, etc.) are never overwritten by upstream — they live next to but outside the symlinked skills/.

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Install (for users)

macOS / Linux / WSL / Git Bash

curl -fsSL https://raw.githubusercontent.com/dqsjqian/agent-commons/main/install.sh | bash

Windows (PowerShell)

iwr -useb https://raw.githubusercontent.com/dqsjqian/agent-commons/main/install.ps1 | iex

The installer does exactly one thing: bootstrap the central directory at ~/.agent-commons/ (or %USERPROFILE%\.agent-commons\) with seed files, then print a bilingual one-liner you can paste into any AI agent. It does not touch any agent's home directory. Agents install themselves — that's the protocol.

Manual install

git clone https://github.com/dqsjqian/agent-commons ~/.agent-commons

Then tell your agent:

"Read ~/.agent-commons/ONBOARDING.md and join Agent Commons."

The agent will figure out how to integrate with itself (symlink, copy, or read-only fallback — see ONBOARDING.md).

(Windows users: replace ~ with $HOME in PowerShell, and use New-Item -ItemType SymbolicLink instead of ln -s.)

Then talk to your agent.

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Platform support

OS / Shell	Status
macOS	✅ first-class
Linux	✅ first-class (any POSIX shell)
Windows + PowerShell 5.1+	✅ first-class (Dev Mode or Admin required for symlinks)
Windows + WSL / Git Bash	✅ works (set MSYS=winsymlinks:nativestrict for Git Bash)
Windows + cmd.exe	❌ not supported (use PowerShell)

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Project status & philosophy

Phase 1 (current): Protocol + reference content. This repo ships the directory skeleton, SKILL.md, manifest.json, and an install script. Less than 200 lines of shell. The README is the product.

Phase 2 (later, if interest): Optional CLI (ac command) for init / link / status / append / doctor. Single-file Python, stdlib only.

Phase 3 (much later): Adapters directory. Community-contributed integration guides for specific agents.

We are deliberately not building:

• a daemon
• a Python/Node package on pip/npm
• a CRDT sync engine
• a cloud service
• a chat UI

This project is a convention, not software. Convention beats configuration. Filesystem beats database. Symlinks beat sync logic.

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License

MIT. See LICENSE.

Author

@dqsjqian · also creator of soul-archive and ai-eight-creed.

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Make your AI agents finally stop forgetting each other.