Skill: milleniumgenai/deep-research-openclaw-agent (version 0.1.1)

--- name: "Deep Research for OpenClaw" description: "Install and wire a structured OpenClaw deep-research sub-agent with hybrid search, artifact-based runs, claim verification, report linting, and validated finalization." version: "0.1.1" metadata: openclaw: homepage: "https://github.com/MilleniumGenAI/deep-research-openclaw-agent" requires: bins: - openclaw - python config: - openclaw.json - deep-researcher agent configured in OpenClaw - Tavily API key configured if Tavily-backed scouting is desired --- # Deep Research for OpenClaw ## What this skill is This is an integration skill for installing and wiring the `deep-researcher` OpenClaw sub-agent from the public repository: - [deep-research-openclaw-agent](https://github.com/MilleniumGenAI/deep-research-openclaw-agent) The repository contains: - the `workspace-researcher` prompt pack; - the local research helper scripts; - the Main -> Deep Research orchestration contract; - the report lint, validation, and finalization pipeline. This skill is intended for OpenClaw users who want a reproducible deep-research workflow without assembling the runtime and contracts from scratch. ## What it can do - structured deep research through `plan -> scout -> harvest -> verify -> synthesize`; - hybrid discovery with `web_search`, Tavily, and `web_fetch`; - explicit source registry, claim ledger, and coverage tracking; - report linting, validation, and final M2M JSON finalization; - honest `SUCCESS | PARTIAL | FAILURE` delivery with explicit gaps and conflicts. ## Requirements - OpenClaw `2026.3.x` or later - Python available on the host - a configured `deep-researcher` agent in OpenClaw - Tavily API access if you want the Tavily-backed path ## Install 1. Clone the repository: - `git clone https://github.com/MilleniumGenAI/deep-research-openclaw-agent.git` 2. Copy `openclaw/workspace-researcher/` into your OpenClaw base directory, or point your agent config at that path directly. 3. Align the main-agent handoff with: - `openclaw/main-deep-research-skill.md` 4. Register or update the `deep-researcher` agent in `openclaw.json`. 5. If you want Tavily-backed scouting, ensure `TAVILY_API_KEY` is available in env or `.env`. ## Validate Run these checks before using the agent in real work: ```bash python -m py_compile openclaw/workspace-researcher/scripts/*.py python openclaw/workspace-researcher/scripts/init_research_run.py --workspace openclaw/workspace-researcher --topic "Smoke test" --language en --task-date 2026-03-10 ``` Then run a first smoke task through OpenClaw once the agent is wired: ```bash openclaw agent --agent deep-researcher --json --message "Perform deep research using your local SOUL.md contract. GOAL: confirm the runtime can initialize a fresh run and return PARTIAL if no external research is performed. SCOPE: in scope is only local init and artifact creation; out of scope is web research. SUCCESS CRITERIA: create fresh tmp artifacts and explain blocked evidence collection honestly. TASK DATE: 2026-03-10. DELIVERABLES: finalized M2M JSON. LANGUAGE: en. CONSTRAINTS: do not fabricate sources; return PARTIAL if evidence is insufficient." ``` ## Core references - Root README: [README.md](https://github.com/MilleniumGenAI/deep-research-openclaw-agent/blob/main/README.md) - Sub-agent contract: [openclaw/workspace-researcher/SOUL.md](https://github.com/MilleniumGenAI/deep-research-openclaw-agent/blob/main/openclaw/workspace-researcher/SOUL.md) - Main handoff contract: [openclaw/main-deep-research-skill.md](https://github.com/MilleniumGenAI/deep-research-openclaw-agent/blob/main/openclaw/main-deep-research-skill.md) - Runtime scripts: [openclaw/workspace-researcher/scripts/](https://github.com/MilleniumGenAI/deep-research-openclaw-agent/tree/main/openclaw/workspace-researcher/scripts) - Agent config template: [openclaw/agent-config.template.json](https://github.com/MilleniumGenAI/deep-research-openclaw-agent/blob/main/openclaw/agent-config.template.json) - Known limits: [docs/known-limits.md](https://github.com/MilleniumGenAI/deep-research-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-researcher/SOUL.md`. - Findings should be built only from traceable external sources, not from local artifacts.


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