Skill: fwang108/scienceclaw-watch (version 1.0.2)

--- name: scienceclaw-watch description: Run a live multi-agent scientific collaboration session and return a full summary when complete. Multiple specialised agents work in parallel, challenge each other's findings, and generate figures. Results and figures are saved to disk and a summary is returned to chat. metadata: {"openclaw": {"emoji": "👁️", "skillKey": "scienceclaw:watch", "requires": {"bins": ["python3"]}, "primaryEnv": "ANTHROPIC_API_KEY"}} --- # ScienceClaw: Watch (Multi-Agent Collaboration Session) Run a parallel multi-agent collaboration session on a scientific topic. Agents work simultaneously, share findings, agree or challenge each other, and produce a rich synthesis with figures. Returns a full summary to chat when the session completes. ## When to use Use this skill when the user asks to: - "Watch agents investigate…" - Run a multi-agent collaboration (not just a single agent) - Get richer, more contested findings where agents push back on each other - Generate figures or visual outputs alongside findings - Run a thorough parallel investigation with 2–5 agents Prefer `scienceclaw-investigate` if the user just wants findings posted to Infinite quickly. Use this skill when they want depth, parallel perspectives, and saved artefacts. ## How it works (Option A: fire-and-forget) The session runs synchronously with `--no-dashboard` so output is fully captured. Results are written to a timestamped output directory. Once complete, the skill reads `session_summary.json` and returns a formatted summary to the user in chat. ## How to run ```bash SCIENCECLAW_DIR="${SCIENCECLAW_DIR:-$HOME/scienceclaw}" TOPIC="<TOPIC>" N_AGENTS=3 TIMESTAMP=$(date +%Y%m%d_%H%M%S) OUTPUT_DIR="$SCIENCECLAW_DIR/run_exports/watch_${TIMESTAMP}" cd "$SCIENCECLAW_DIR" source .venv/bin/activate 2>/dev/null || true python3 bin/scienceclaw-watch \ "$TOPIC" \ --agents "$N_AGENTS" \ --output "$OUTPUT_DIR" \ --no-dashboard \ --timeout 60 ``` Then read the summary: ```bash cat "$OUTPUT_DIR/session_summary.json" ``` ### Parameters - `TOPIC` — the research topic (required). Use the user's exact phrasing. - `--agents N` — number of agents to spawn (1–5, default: 3). Use 2 for speed, 4–5 for depth. - `--output DIR` — where to save results and figures. Always set this to a timestamped path under `run_exports/` so results are organised. - `--no-dashboard` — **always include this**. Disables the Rich live UI so output is captured cleanly. - `--timeout SEC` — per-tool timeout in seconds (default: 45). Increase to 90–120 for complex topics. - `--session-id` — optional custom session ID for tracking. ### Example invocations ```bash # Standard 3-agent session cd ~/scienceclaw && python3 bin/scienceclaw-watch \ "BACE1 inhibitors for Alzheimer's disease" \ --agents 3 --no-dashboard \ --output run_exports/watch_$(date +%Y%m%d_%H%M%S) \ --timeout 60 # Quick 2-agent session cd ~/scienceclaw && python3 bin/scienceclaw-watch \ "ibrutinib resistance in CLL" \ --agents 2 --no-dashboard \ --output run_exports/watch_$(date +%Y%m%d_%H%M%S) \ --timeout 45 # Deep 5-agent session with longer timeout cd ~/scienceclaw && python3 bin/scienceclaw-watch \ "multi-target kinase inhibitors for glioblastoma" \ --agents 5 --no-dashboard \ --output run_exports/watch_$(date +%Y%m%d_%H%M%S) \ --timeout 120 ``` ## Reading the results After the session completes, parse `session_summary.json` in the output directory. It contains: ```json { "topic": "...", "agents": ["Agent1", "Agent2", "Agent3"], "findings": [{"text": "...", "sources": ["AgentName"]}], "figures": [{"path": "..."}], "challenges": 4, "agreements": 7, "output_dir": "..." } ``` ## Workspace context injection Before running, check if the user's workspace memory contains project context: - Read `memory.md` in the workspace for stored research focus, organism, compound, or target - If found, append context to the topic string: e.g. `"BACE1 inhibitors [project context: NSCLC, BBB penetration focus]"` ## After running Report back to the user with a structured summary: - **Agents** that participated (list them) - **Key findings** — top 5, with the agent that found each one: `[AgentName] finding text` - **Agreements** and **challenges** count (e.g. "7 agreements, 4 challenges between agents") - **Figures generated** — list file paths or names - **Results saved to** — the output directory path - Offer follow-up options: - "Want me to post the synthesis to Infinite?" → use `scienceclaw-post` - "Want to investigate a specific finding deeper?" → use `scienceclaw-investigate`


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