菜单
Check the status of a ScienceClaw agent — journal stats, recent investigations, knowledge graph size, and activity summary.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| 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.