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coder-openclaw-agent skill

/skills/milleniumgenai/coder-openclaw-agent

This skill installs and wires a coding-focused OpenClaw sub-agent for background coding, testing, and data-analysis tasks.

npx playbooks add skill openclaw/skills --skill coder-openclaw-agent

Review the files below or copy the command above to add this skill to your agents.

Files (2)
SKILL.md
3.7 KB
---
name: "Coder for OpenClaw"
description: "Install and wire a coding-focused OpenClaw sub-agent for background code execution, test-driven edits, bug fixing, small project scaffolding, and small-to-medium data-analysis tasks."
version: "0.1.3"
metadata:
  openclaw:
    homepage: "https://github.com/MilleniumGenAI/coder-openclaw-agent"
    requires:
      bins:
        - openclaw
        - docker
        - git
      config:
        - openclaw.json
        - openai-codex provider profile configured in OpenClaw
---

# Coder for OpenClaw

## What this skill is
This is an integration skill for installing and wiring the `coder` OpenClaw sub-agent from the public repository:

- [coder-openclaw-agent](https://github.com/MilleniumGenAI/coder-openclaw-agent)

The repository contains:
- the `workspace-coder` prompt pack;
- the `coder-sandbox:latest` Docker image definition;
- the `coder` agent config template;
- the Main -> Coder orchestration contract.

This skill is intended for OpenClaw users who want a strong background coding and data-analysis sub-agent without building the orchestration from scratch.

## What it can do
- code execution and verification inside the OpenClaw sandbox;
- bug fixing and test-driven edits;
- small project scaffolding;
- small-to-medium data-analysis tasks;
- HTML, PDF, spreadsheet, and office-style document processing;
- honest blocked-state reporting through `PARTIAL` or `FAILURE`.

## Requirements
- OpenClaw `2026.3.x` or later
- Docker available on the host
- an authenticated `openai-codex` provider profile

## Install
1. Clone the repository:
   - `git clone https://github.com/MilleniumGenAI/coder-openclaw-agent.git`
2. Copy `openclaw/workspace-coder/` into your OpenClaw base directory, or point your agent config at that path directly.
3. Build the sandbox image from the repository root:
   - `docker build -f docker/coder-sandbox.dockerfile -t coder-sandbox:latest .`
4. Register the agent in `openclaw.json` using:
   - `openclaw/agent-config.template.json`
5. If your main agent delegates coding tasks, align it with:
   - `openclaw/main-coder-prompt.md`

## Validate
Run these checks before using the agent in real work:

```bash
openclaw models status --agent coder --probe --probe-provider openai-codex --json
openclaw sandbox explain --agent coder
```

Then run a first smoke task:

```bash
openclaw agent --agent coder --json --message "Return strictly valid JSON matching coder SOUL schema. GOAL: create /tmp/coder/smoke/main.py that prints hello. INPUTS: none. CONSTRAINTS: work only in /tmp/coder/smoke; use python3 and Linux/bash commands only; use PARTIAL if blocked. SUCCESS CRITERIA: python3 /tmp/coder/smoke/main.py prints hello. DELIVERABLES: codeblocks and sandbox_log."
```

## Core references
- Root README: [README.md](https://github.com/MilleniumGenAI/coder-openclaw-agent/blob/main/README.md)
- Agent config template: [openclaw/agent-config.template.json](https://github.com/MilleniumGenAI/coder-openclaw-agent/blob/main/openclaw/agent-config.template.json)
- Main -> Coder orchestration guide: [openclaw/main-coder-prompt.md](https://github.com/MilleniumGenAI/coder-openclaw-agent/blob/main/openclaw/main-coder-prompt.md)
- Runtime inventory: [docker/RUNTIME.md](https://github.com/MilleniumGenAI/coder-openclaw-agent/blob/main/docker/RUNTIME.md)
- Known limits: [docs/known-limits.md](https://github.com/MilleniumGenAI/coder-openclaw-agent/blob/main/docs/known-limits.md)

## Notes
- This is an OpenClaw-only v1 package.
- ClawHub publishes skills under platform-wide MIT-0 terms.
- The runtime source of truth is `openclaw/workspace-coder/SOUL.md`.
- Default working area inside the sandbox is `/tmp/coder/<task_name>/`.
- The expected output contract is strict JSON with `SUCCESS | PARTIAL | FAILURE`.

Overview

This skill installs and wires a coding-focused OpenClaw sub-agent named Coder for background code execution, test-driven edits, bug fixing, small project scaffolding, and small-to-medium data analysis. It provides a ready-made sandbox image, prompt pack, and agent configuration to avoid building orchestration from scratch. The agent reports honest blocked states using PARTIAL or FAILURE and expects strict JSON output for success reporting.

How this skill works

The skill adds a Coder sub-agent that runs tasks inside a Docker-based sandbox where code can be executed, tested, and verified. It supplies a workspace prompt pack, a sandbox runtime image, and an agent config template so the main OpenClaw agent can delegate coding work. Tasks run in an isolated working area and return structured JSON with SUCCESS, PARTIAL, or FAILURE and include sandbox logs and deliverables.

When to use it

  • Add background code execution and automated test-driven edits to an OpenClaw deployment
  • Automate bug fixes, small project scaffolds, or incremental code changes
  • Run small-to-medium data-analysis jobs that require execution inside a reproducible sandbox
  • Process HTML, PDF, spreadsheet, or office-style documents programmatically
  • Require explicit blocked-state reporting (PARTIAL/FAILURE) for safe orchestration

Best practices

  • Run on OpenClaw 2026.3.x or later with Docker available on the host
  • Provide an authenticated openai-codex provider profile for model execution
  • Keep tasks scoped to the default working area (/tmp/coder/<task_name>/) for reproducibility
  • Validate the agent with the provided model and sandbox probes before production use
  • Align the main agent’s delegation prompts with the Coder orchestration contract to avoid misrouting

Example use cases

  • Smoke-test code execution by creating a small script that prints a string and returning the sandbox log
  • Automatically fix failing unit tests using test-driven edits inside the sandbox
  • Scaffold a small CLI project with template files, setup, and basic tests
  • Run a multi-step data-cleaning and analysis pipeline on a medium-sized CSV and return processed outputs
  • Extract data from PDFs or spreadsheets and convert results into structured JSON or CSV

FAQ

What runtime prerequisites are required?

OpenClaw 2026.3.x or later, Docker on the host, and an authenticated openai-codex provider profile.

How does the agent indicate it is blocked?

The agent uses PARTIAL or FAILURE in the strict JSON result contract to report blocked or unrecoverable states.