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Polyphony

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alinaqi
polyphony

Multi-agent orchestration with container-isolated workspaces — each agent session runs in its own Docker container with independent git branches

Overview

Publisheralinaqi
Repositorymaggy
Skill namepolyphony
Stars
707
Forks
57
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by alinaqi on GitHub. Read the source before you install it.

Installation

Install the Polyphony AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/alinaqi/maggy/tree/main/skills/polyphony
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/alinaqi/maggy.git /tmp/maggy
mkdir -p .claude/skills
cp -r /tmp/maggy/skills/polyphony .claude/skills/polyphony
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Polyphony in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Polyphony on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Polyphony is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Polyphony — Multi-Agent Orchestration

Container-isolated workspaces for parallel agent execution. Each agent gets its own Docker container with a full git clone on its own branch. No conflicts, independent tests, clean PRs.


Architecture (6 Layers)

  1. Work Source — Tasks from GitHub Issues (gh api) or local SQLite queue
  2. Orchestrator — Supervisor loop: discover -> claim -> route -> provision -> run -> verify -> land
  3. Router — Pure function: Task x Policy -> RunSpec (5-dimension complexity scoring)
  4. Identity Broker — Resolves named credentials to volume mounts + env overlays
  5. Workspace Manager — Per-task git clone --reference, branch checkout, cleanup
  6. Worker Runtime — Docker container create/start/stop/logs lifecycle

Task Lifecycle

DISCOVERED -> CLAIMED -> ROUTED -> PROVISIONED -> RUNNING -> VERIFYING -> LANDED
                                                     |           |
                                                     v           v
                                                   FAILED --> BLOCKED
                                                     |
                                                     v
                                                   CLAIMED (retry)

Prerequisites

  • Docker or OrbStack installed and running
  • At least one agent CLI available (Claude, Codex, or Kimi)
  • CLI subscriptions configured (not API keys)

Check:

bash
command -v docker &>/dev/null || command -v orbctl &>/dev/null

Configuration

All config lives in ~/.polyphony/:

FilePurpose
config.yamlWorkspace root, poll interval, max concurrency
identities.yamlNamed credential bundles with volume paths
agents.yamlAgent profiles (CLI commands, strengths)
routing.yamlRouting rules and fallback chains

Initialize with: polyphony init


Routing Rules

Rules are evaluated top-down; first match wins. Each rule has a match predicate and an agent target.

yaml
rules:
  - match: { task_type: docs, risk: low }
    agent: kimi
  - match: { task_type: bugfix }
    agent: codex
  - match: { risk: high }
    agent: claude
default:
  agent: claude
  fallback: [codex, kimi]

Complexity Scoring (5 Dimensions)

Each dimension scores 0-2. Total 0-10.

DimensionSource
Cyclomatic depthLOC + scope size
Fan-outNumber of callers
Security boundaryAuth/PII keywords
ConcurrencyLock/transaction keywords
Domain invariantsRisk level + task type

Routing thresholds:

  • 0-3: Delegate to Kimi solo
  • 4-6: Kimi + Codex review
  • 7-10: Claude direct

Container Isolation

Each task gets:

  • Its own Docker container from polyphony-worker:latest
  • A full git clone at /workspace (not a worktree)
  • Auth volumes mounted read-only (e.g., ~/.claude:/home/worker/.claude:ro)
  • Independent test execution
  • Its own branch for PRs

CLI Commands

bash
polyphony init                    # Create ~/.polyphony/ with config templates
polyphony spawn "Fix auth bug"    # Create and route a task
polyphony status                  # Show task states
polyphony cleanup                 # Remove completed workspaces

Integration with Existing Skills

  • cross-agent-delegation: Uses Polyphony's complexity scoring for routing decisions
  • agent-teams: Uses Polyphony's workspace isolation instead of shared directories
  • spawn-team: Uses Polyphony's container provisioning for feature agents

Frequently asked questions

What does the Polyphony AI skill do?

Multi-agent orchestration with container-isolated workspaces — each agent session runs in its own Docker container with independent git branches

Why use Polyphony on TypingMind?

Because you install it once and use it with any model. Polyphony is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Polyphony in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/alinaqi/maggy/tree/main/skills/polyphony. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Polyphony?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Polyphony?

As many as you like. As long as a model supports skills, you can use Polyphony with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Polyphony AI skill free?

Yes. It is published on GitHub by alinaqi under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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