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Check the status of a ScienceClaw agent — journal stats, recent investigations, knowledge graph size, and activity summary.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | scienceclaw-status |
| description | Check the status of a ScienceClaw agent — journal stats, recent investigations, knowledge graph size, and activity summary. |
| metadata | {"openclaw":{"emoji":"📊","skillKey":"scienceclaw:status","requires":{"bins":["python3"]},"primaryEnv":"ANTHROPIC_API_KEY"}} |
Inspect the memory, activity, and health of a ScienceClaw agent.
Use this skill when the user asks to:
Use bash to invoke the memory CLI. SCIENCECLAW_DIR defaults to ~/scienceclaw or ~/.scienceclaw/install.
SCIENCECLAW_DIR="${SCIENCECLAW_DIR:-$HOME/scienceclaw}"
AGENT=$(python3 -c "import json,pathlib; p=pathlib.Path.home()/'.scienceclaw'/'agent_profile.json'; print(json.loads(p.read_text()).get('name','ScienceAgent'))" 2>/dev/null || echo "ScienceAgent")
cd "$SCIENCECLAW_DIR"
python3 memory_cli stats --agent "$AGENT"
python3 memory_cli journal --agent "$AGENT"
python3 memory_cli journal --agent "$AGENT" --recent 10
python3 memory_cli investigations --agent "$AGENT" --active
python3 memory_cli journal --agent "$AGENT" --topics
python3 memory_cli graph --agent "$AGENT" --search "CRISPR"
python3 memory_cli stats --agent "$AGENT"
--agent — agent name (auto-resolved from ~/.scienceclaw/agent_profile.json if not provided)--recent N — show last N journal entries--active — show only in-progress investigations--search TERM — search knowledge graph for a term--topics — list all topics ever investigatedAlways auto-resolve the agent name from the profile before running:
AGENT=$(python3 -c "
import json, pathlib
p = pathlib.Path.home() / '.scienceclaw' / 'agent_profile.json'
print(json.loads(p.read_text()).get('name', 'ScienceAgent'))
" 2>/dev/null || echo "ScienceAgent")
If the user specifies an agent name explicitly, use that instead.
If the workspace memory (memory.md) contains a preferred agent name, use that as the default --agent value.
Report back to the user:
scienceclaw-investigate on any of the listed topicsOnboard and manage Paperclip AI for research-paper knowledge and agent orchestration
Generate a structured scientific post and publish it to Infinite. Runs a focused single-agent investigation (PubMed search → LLM analysis → hypothesis/method/findings/conclusion) and posts the result. Faster than scienceclaw-investigate — best for targeted, single-topic posts.
Infinite platform integration for AI agent collaboration
Read a CSV or XLSX file and return columns, shape, dtypes, and first N rows as JSON.
Execute arbitrary Python code and return stdout. NumPy, pandas, scipy, matplotlib, and other scientific libraries are available.
Generate a structured scientific PDF report from a JSON description. Accepts a JSON file specifying title, authors, abstract, sections (headings, text, tables, figures), and inline data panels (heatmap, bar, scatter, line). Produces a publication-style A4 PDF using reportlab with no LaTeX dependency. All figures are either loaded from PNG paths or generated on-the-fly from inline data.