AI Worker worker.md

agentao

Local-first, governed AI agent runtime for Python — embed it in your app, or run it as a CLI or ACP server. Permissions, MCP, memory and audit replay built in.

Tool registry 304 stars Python MIT Worker-compatible

Source#

  • Repository: jin-bo/agentao
  • Last source update: 2026-09-20
  • Last verified: 2026-09-20

Tags#

acpagent-frameworkai-agentclillmlocal-first

Integration notes#

Repository is focused on tool/server interoperability; wrap in bounded worker contracts for production use.

worker.md example#

Starter worker.md contract mapped from this registry entry. Copy this file and adapt schemas, constraints, and statuses for your task.

---
id: agentao-repo-derived-worker
name: agentao Repo-Derived Worker
version: 1.0.0
source_registry_url: https://worker.md/registry/agentao/
source_repository: https://github.com/jin-bo/agentao
repository_default_branch: main
repository_language: Python
repository_license: MIT
repository_updated_at: 2026-09-20
worker_mode: tool-gateway-worker
derivation_method: github_repository_metadata_plus_raw_readme
derivation_confidence: 0.95
derived_on: 2026-09-20
tags:
  - acp
  - agent-framework
  - ai-agent
  - cli
  - llm
  - local-first
---

# agentao Repo-Derived Worker

## Repo-derived summary
- Registry summary: Local-first, governed AI agent runtime for Python — embed it in your app, or run it as a CLI or ACP server. Permissions, MCP, memory and audit replay built in.
- Repository description: Local-first, governed AI agent runtime for Python — embed it in your app, or run it as a CLI or ACP server. Permissions, MCP, memory and audit replay built in.
- Stars (snapshot): 304
- Primary language: Python
- Worker mode classification: tool-gateway-worker

## Extracted from
- https://github.com/jin-bo/agentao
- https://github.com/jin-bo/agentao/blob/main/README.md
- https://agentao.cn
- https://agentao.cn/en/cli/
- https://agentao.cn/zh/cli/

## Evidence notes (from repository text)
- README summary paragraph: > **"Order in Chaos, Path in Intelligence."** > > **Agentao** is a **Governed Agent Runtime** — a local-first, private-first, embeddable agent harness for Python hosts. Permissions, protocols, memory, plugins, and multi-session control are all first-class.
- > **Agentao** is a **Governed Agent Runtime** — a local-first, private-first, embeddable agent harness for Python hosts. Permissions, protocols, memory, plugins, and multi-session control are all first-class.
- The full handbook lives in `developer-guide/` (VitePress, bilingual). Production site: **https://agentao.cn**.
- | **Coding agents** — Claude Code / Codex / … embedding Agentao into another project | [`docs/guides/embed-for-agents.md`](docs/guides/embed-for-agents.md) (distilled, copy-paste playbook) | — |
- | **CLI users** — driving `agentao` in the terminal | [`developer-guide/en/cli/`](developer-guide/en/cli/) (12 chapters: slash commands · plan mode · memory · replay · …) | https://agentao.cn/en/cli/ |
- | **Embedding developers** — building Agentao into your app | [`developer-guide/en/`](developer-guide/en/) (Parts 1–7 + Appendix) | https://agentao.cn |

## Installation hints found in README
- `pip install agentao`
- `pip install 'agentao[cli]'`
- `pip install 'agentao[full]'` for zero behaviour change. See [docs/migration/0.3.x-to-0.4.0.md](docs/migration/0.3.x-to-0.4.0.md).`
- `pip install 'agentao[full]'`

## worker.md contract (derived starter)
Purpose: Expose repository-supported tool/server capabilities behind a bounded worker interface.

### Input schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "request_id",
    "operation",
    "payload"
  ],
  "properties": {
    "request_id": {
      "type": "string"
    },
    "operation": {
      "type": "string"
    },
    "payload": {
      "type": "object"
    }
  }
}
```

### Output schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "request_id",
    "status",
    "result"
  ],
  "properties": {
    "request_id": {
      "type": "string"
    },
    "status": {
      "type": "string",
      "enum": [
        "ok",
        "retryable_error",
        "invalid_request",
        "invalid_output"
      ]
    },
    "result": {
      "type": "object"
    }
  }
}
```

### Constraints
- timeout_seconds: 30
- max_attempts: 2
- idempotency_key: request_id
- status_enum: [ok, retryable_error, invalid_request, invalid_output]
- notes: adapt to concrete APIs/classes documented in this repository before production use

## How this should be used
1. Treat this file as a repo-derived starter profile, not a claim of an official repository API contract.
2. Replace schemas with exact interfaces from code/docs you adopt.
3. Keep execution bounded and auditable using worker protocol constraints.

How to use#

  • Save this as a worker spec file (for example: agentao-my-task.worker.md).
  • Replace the input/output schemas and purpose with your real bounded task.
  • Enforce schema validation + timeout + retry policy in your runtime before production use.

Citation#

Reference URL: https://worker.md/registry/agentao/

Source URL: https://github.com/jin-bo/agentao