Bohan Jiang
e0e91fc792
* feat(daemon): harden agent mention-loop instructions Two agents that mention each other via `mention://agent/<id>` can fall into an infinite reply loop — each says "I'm done" in prose but keeps `@mentioning` the other, which re-enqueues their run. Adding hard caps on agent-to-agent turns conflicts with Multica's design principle of giving agents the same authorship freedom as humans, so this change hardens the instructions that the harness injects instead. - Replace the terse "mentions are actions" blurb with a full Mentions protocol: `side-effecting` warning, explicit "when NOT to mention" (replying to another agent, sign-offs, thanks) and "when a mention IS appropriate" (human escalation, first-time delegation, user asked). - Add a pre-workflow decision step for comment-triggered runs: decide whether a reply is warranted at all, decide whether to include any `@mention`, and clarify that the post-a-comment rule is mandatory *if* you reply — silence is a valid exit for agent-to-agent threads. - Thread the triggering comment's author kind + display name (`TriggerAuthorType` / `TriggerAuthorName`) from the claim endpoint through the daemon task type, per-turn prompt, and CLAUDE.md workflow. When the author is another agent, both surfaces now name that agent and warn against sign-off mentions. - Soften the old closing line that told agents to `always` use the mention format — the word generalized to member/agent mentions and encouraged the very behavior that causes loops. Refs GH#1576, MUL-1323. * fix(daemon): remove MUST-respond conflict and sanitize trigger author name Addresses two blocking points on PR #1581: 1. buildCommentPrompt told the agent "You MUST respond to THIS comment" and unconditionally appended the reply command — directly conflicting with the new agent-to-agent silence-as-valid-exit workflow. Models were likely to keep following the older must-reply rule and fall back into the loop this PR is trying to close. Rewrite the header as "Focus on THIS comment — do not confuse it with previous ones" (keeps the anti-stale-comment signal) and change BuildCommentReplyInstructions to open with "If you decide to reply, post it by running exactly this command" so the reply command is available but conditional across both prompt surfaces. 2. Raw agent/user display names were being embedded directly into the high-priority prompt and CLAUDE.md via TriggerAuthorName. Agent and member names are only validated as non-empty at write time, so a name containing newlines, backticks, or fake mention markup would turn the field into a cross-agent prompt-injection surface. Add execenv.SanitizePromptField — strip control runes, collapse whitespace, drop markdown structural characters (backtick, asterisk, brackets, pipe, angle brackets, hash, backslash), truncate to 64 runes — and apply it at both embed sites (per-turn prompt and CLAUDE.md). Defense-in-depth at the consumption layer so this works for already-stored names without a migration. Tests: TestSanitizePromptField covers the policy; TestBuildPromptSanitizesAgentName plants an attack payload in TriggerAuthorName and checks the rendered prompt does not leak the newline-anchored injection or the fake mention markup. TestBuildPromptCommentTriggered*{,ByMember} updated to lock in the conditional reply-command framing. * refactor(daemon): trim redundant CLAUDE.md preamble and drop name sanitizer Per PR #1581 feedback: 1. Remove the `if ctx.TriggerAuthorType == "agent"` preamble block in runtime_config.go. It duplicated what workflow steps 4 and 5 already say ("Decide whether a reply is warranted", "Never @mention the agent you are replying to as a thank-you or sign-off"), so the signal lands the same without the extra ~7 lines of CLAUDE.md. The per-turn prompt preamble in prompt.go stays — that surface has no numbered workflow below it and would otherwise lose the silence-as-exit signal. 2. Delete execenv.SanitizePromptField + its test. Workspace agents are created by trusted team members, so the cross-agent name-injection surface it defended isn't realistic in the current trust model. 3. Drop TriggerAuthorType/Name from execenv.TaskContextForEnv and stop populating them in daemon.go — they're no longer read by the execenv package. The same fields on daemon.Task stay because prompt.go still needs them to label the triggering author in the per-turn prompt. Tests simplified to match the leaner shape: CLAUDE.md regression guards now assert that the anti-loop phrases live in the numbered workflow, and the sanitizer-specific tests are removed.
Multica
Your next 10 hires won't be human.
The open-source managed agents platform.
Turn coding agents into real teammates — assign tasks, track progress, compound skills.
Website · Cloud · X · Self-Hosting · Contributing
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What is Multica?
Multica turns coding agents into real teammates. Assign issues to an agent like you'd assign to a colleague — they'll pick up the work, write code, report blockers, and update statuses autonomously.
No more copy-pasting prompts. No more babysitting runs. Your agents show up on the board, participate in conversations, and compound reusable skills over time. Think of it as open-source infrastructure for managed agents — vendor-neutral, self-hosted, and designed for human + AI teams. Works with Claude Code, Codex, OpenClaw, OpenCode, Hermes, Gemini, Pi, and Cursor Agent.
Features
Multica manages the full agent lifecycle: from task assignment to execution monitoring to skill reuse.
- Agents as Teammates — assign to an agent like you'd assign to a colleague. They have profiles, show up on the board, post comments, create issues, and report blockers proactively.
- Autonomous Execution — set it and forget it. Full task lifecycle management (enqueue, claim, start, complete/fail) with real-time progress streaming via WebSocket.
- Reusable Skills — every solution becomes a reusable skill for the whole team. Deployments, migrations, code reviews — skills compound your team's capabilities over time.
- Unified Runtimes — one dashboard for all your compute. Local daemons and cloud runtimes, auto-detection of available CLIs, real-time monitoring.
- Multi-Workspace — organize work across teams with workspace-level isolation. Each workspace has its own agents, issues, and settings.
Quick Install
macOS / Linux (Homebrew - recommended)
brew install multica-ai/tap/multica
Use brew upgrade multica-ai/tap/multica to keep the CLI current.
macOS / Linux (install script)
curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash
Use this if Homebrew is not available. The script installs the Multica CLI on macOS and Linux by using Homebrew when it is on PATH, otherwise it downloads the binary directly.
Windows (PowerShell)
irm https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.ps1 | iex
Then configure, authenticate, and start the daemon in one command:
multica setup # Connect to Multica Cloud, log in, start daemon
Self-hosting? Add
--with-serverto deploy a full Multica server on your machine:curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash -s -- --with-server multica setup self-hostThis pulls the official Multica images from GHCR (latest stable by default). Requires Docker. See the Self-Hosting Guide for details. If the selected GHCR tag has not been published yet, fall back to
make selfhost-buildfrom a checkout.
Getting Started
1. Set up and start the daemon
multica setup # Configure, authenticate, and start the daemon
The daemon runs in the background and auto-detects agent CLIs (claude, codex, openclaw, opencode, hermes, gemini, pi, cursor-agent) on your PATH.
2. Verify your runtime
Open your workspace in the Multica web app. Navigate to Settings → Runtimes — you should see your machine listed as an active Runtime.
What is a Runtime? A Runtime is a compute environment that can execute agent tasks. It can be your local machine (via the daemon) or a cloud instance. Each runtime reports which agent CLIs are available, so Multica knows where to route work.
3. Create an agent
Go to Settings → Agents and click New Agent. Pick the runtime you just connected and choose a provider (Claude Code, Codex, OpenClaw, OpenCode, Hermes, Gemini, Pi, or Cursor Agent). Give your agent a name — this is how it will appear on the board, in comments, and in assignments.
4. Assign your first task
Create an issue from the board (or via multica issue create), then assign it to your new agent. The agent will automatically pick up the task, execute it on your runtime, and report progress — just like a human teammate.
Multica vs Paperclip
| Multica | Paperclip | |
|---|---|---|
| Focus | Team AI agent collaboration platform | Solo AI agent company simulator |
| User model | Multi-user teams with roles & permissions | Single board operator |
| Agent interaction | Issues + Chat conversations | Issues + Heartbeat |
| Deployment | Cloud-first | Local-first |
| Management depth | Lightweight (Issues / Projects / Labels) | Heavy governance (Org chart / Approvals / Budgets) |
| Extensibility | Skills system | Skills + Plugin system |
TL;DR — Multica is built for teams that want to collaborate with AI agents on real projects together.
CLI
The multica CLI connects your local machine to Multica — authenticate, manage workspaces, and run the agent daemon.
| Command | Description |
|---|---|
multica login |
Authenticate (opens browser) |
multica daemon start |
Start the local agent runtime |
multica daemon status |
Check daemon status |
multica setup |
One-command setup for Multica Cloud (configure + login + start daemon) |
multica setup self-host |
Same, but for self-hosted deployments |
multica issue list |
List issues in your workspace |
multica issue create |
Create a new issue |
multica update |
Update to the latest version |
See the CLI and Daemon Guide for the full command reference.
Architecture
┌──────────────┐ ┌──────────────┐ ┌──────────────────┐
│ Next.js │────>│ Go Backend │────>│ PostgreSQL │
│ Frontend │<────│ (Chi + WS) │<────│ (pgvector) │
└──────────────┘ └──────┬───────┘ └──────────────────┘
│
┌──────┴───────┐
│ Agent Daemon │ runs on your machine
└──────────────┘ (Claude Code, Codex, OpenCode,
OpenClaw, Hermes, Gemini,
Pi, Cursor Agent)
| Layer | Stack |
|---|---|
| Frontend | Next.js 16 (App Router) |
| Backend | Go (Chi router, sqlc, gorilla/websocket) |
| Database | PostgreSQL 17 with pgvector |
| Agent Runtime | Local daemon executing Claude Code, Codex, OpenClaw, OpenCode, Hermes, Gemini, Pi, or Cursor Agent |
Development
For contributors working on the Multica codebase, see the Contributing Guide.
Prerequisites: Node.js v20+, pnpm v10.28+, Go v1.26+, Docker
make dev
make dev auto-detects your environment (main checkout or worktree), creates the env file, installs dependencies, sets up the database, runs migrations, and starts all services.
See CONTRIBUTING.md for the full development workflow, worktree support, testing, and troubleshooting.