Skill: chonknick/chonkie-deepresearch (version 1.1.0)

--- name: chonkie-deepresearch description: "Run deep research queries using Chonkie DeepResearch. Returns comprehensive research reports with citations — useful for market analysis, competitive intelligence, technical deep dives, and any research-heavy task." homepage: https://chonkie.ai metadata: { "openclaw": { "emoji": "🔬", "requires": { "bins": ["chdr"] }, "tags": ["research", "deep-research", "analysis", "reports", "chonkie"] } } --- # Chonkie DeepResearch Run deep research queries from your agent and get comprehensive reports with citations. ## Setup Before using, check if `chdr` is installed (`which chdr`). If not: 1. Install: `cargo install chdr` - If `cargo` isn't available, install Rust first: `curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh` 2. Authenticate: `chdr auth login` (opens browser to get an API key) - Or set `CHONKIE_API_KEY` environment variable - Get a key at https://labs.chonkie.ai/settings/api-keys ## Usage **IMPORTANT: Research takes 2-10 minutes. Always spawn a sub-agent to avoid blocking the main thread.** ### Running research (recommended: sub-agent) Use `sessions_spawn` to run the research in a sub-agent. The sub-agent handles the long-running query and announces the result when done, so your main agent stays responsive. ```json { "tool": "sessions_spawn", "task": "Run chdr research and save results. Steps:\n1. Run: chdr research --type report --no-stream --json \"<QUERY>\" > /tmp/chdr-research-<TIMESTAMP>.json\n2. Extract ID and title: python3 -c \"import json; d=json.load(open('/tmp/chdr-research-<TIMESTAMP>.json')); print(d['id']); print(d.get('title','Untitled'))\"\n3. Extract body: python3 -c \"import json; d=json.load(open('/tmp/chdr-research-<TIMESTAMP>.json')); print(d.get('content',{}).get('body',''))\" > /tmp/chdr-research-<TIMESTAMP>.md\n4. Report back the title, ID, and URL: https://labs.chonkie.ai/research/{id}" } ``` Replace `<QUERY>` with the research query and `<TIMESTAMP>` with `$(date +%s)`. ### Monitoring research status **Do NOT poll continuously for status.** Instead, set up a cron job to check periodically (every 2-3 minutes): ```bash # Add a cron entry to check research status every 2 minutes # The cron should run: chdr view <id> --json | python3 -c "import json,sys; d=json.load(sys.stdin); s=d.get('status','unknown'); print(s)" # and notify you when status is 'completed' or 'failed' ``` Or simply wait for the sub-agent to announce completion — it will report back automatically when the research finishes. The sub-agent approach is preferred over cron for one-off research queries. ### After research completes When the sub-agent announces completion: 1. The web URL is: `https://labs.chonkie.ai/research/{id}` 2. The full report is saved at `/tmp/chdr-research-<TIMESTAMP>.md` 3. Read only the first 100 lines for a summary — NEVER load the entire file 4. Tell the user you can answer questions about the report ### Answering follow-up questions - Grep the `.md` file to find relevant sections before reading - Use offset/limit to read only the matching section - NEVER read the entire file into context — reports can be 20,000+ lines ### Fallback: running without sub-agent If sub-agents are unavailable, run the research command directly but warn the user it will block for several minutes: ```bash chdr research --type report --no-stream --json "<query>" > /tmp/chdr-research.json ``` ### Other commands ```bash chdr ls # List recent research chdr ls --limit 20 # List more chdr view <id> # View a report (supports partial ID prefix) chdr open <id> # Open in browser chdr delete <id> # Delete a report ``` All commands that take an ID support prefix matching — `chdr view 3a6b` works if unambiguous.


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