Skill: milleniumgenai/coder-openclaw-agent (version 0.1.3)

--- 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`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)