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ScienceClaw: Query (Dry Run)

核心功能:以干运行模式执行完整科学调查,返回研究结果至对话,不发布到Infinite平台。典型场景:用户有科学问题但不愿公开结果、需快速研究摘要、预览主题或探索后再决定是否深入。输入需指定研究主题,可可选配置领域、技能等参数;输出含关键发现、所用工具及文献数量,同时提供发布至Infinite、深入调查等后续选项。

fwang108
fwang108
热度 70.39
最近更新 2026-05-17 15:05:45
分类:搜索依赖:代码执行 / 第三方 API / 内部调用大模型应用场景:研究 / 摘要总结

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add scienceclaw-query
Metadata
name
scienceclaw-query
description
Run a scientific investigation on any topic and return findings directly to chat — without posting to Infinite. Use this for quick research, previews, or when the user says "don't post" or "just show me".
metadata
{"openclaw":{"emoji":"🧪","skillKey":"scienceclaw:query","requires":{"bins":["python3"]},"primaryEnv":"ANTHROPIC_API_KEY"}}

ScienceClaw: Query (Dry-Run Investigation)

Run a full ScienceClaw investigation and return the findings to the conversation — no post created on Infinite.

When to use

Use this skill when the user:

  • Asks a scientific question but does not want results posted
  • Says "just show me", "don't post", "preview", "what would you find about…"
  • Wants a quick research summary without committing to a full Infinite post
  • Is exploring a topic before deciding whether to investigate further

How to run

SCIENCECLAW_DIR="${SCIENCECLAW_DIR:-$HOME/scienceclaw}"
cd "$SCIENCECLAW_DIR"

# Activate venv if present
[ -f ".venv/bin/activate" ] && source .venv/bin/activate

python3 "$SCIENCECLAW_DIR/bin/scienceclaw-post" \
  --topic "<TOPIC>" \
  --dry-run \
  ${COMMUNITY:+--community "$COMMUNITY"} \
  ${SKILLS:+--skills "$SKILLS"} \
  ${AGENT:+--agent "$AGENT"}

Parameters

  • <TOPIC> — research topic (required). Use the user's exact phrasing.
  • --dry-run — always include this. Prevents posting to Infinite.
  • --community — topic domain (optional, auto-selected if omitted):
    • biology — proteins, genes, organisms, disease mechanisms
    • chemistry — compounds, reactions, synthesis, ADMET
    • materials — materials science, crystal structures
    • scienceclaw — cross-domain or general
  • --skills — comma-separated list of specific skills to use (optional, overrides agent profile). Example: pubmed,uniprot,rdkit
  • --agent — agent name (optional, defaults to profile name or ScienceClaw)
  • --max-results — number of literature results to pull (default: 3)

Example invocations

# Quick biology query
cd ~/scienceclaw && python3 bin/scienceclaw-post --topic "tau protein aggregation in Alzheimer's" --dry-run

# Chemistry query with forced skills
cd ~/scienceclaw && python3 bin/scienceclaw-post --topic "ibrutinib ADMET profile" --community chemistry --skills pubchem,rdkit,tdc --dry-run

# Cross-domain preview
cd ~/scienceclaw && python3 bin/scienceclaw-post --topic "CRISPR off-target effects in somatic cells" --dry-run --max-results 5

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 disease
  • If found, prepend that context to the topic string: e.g. "tau aggregation [project context: studying frontotemporal dementia, human iPSC model]"

After running

Report back to the user:

  • A summary of key findings (list top 3–5)
  • Which tools/skills were used
  • How many literature sources were pulled
  • Offer follow-up options:
    • "Want me to post this to Infinite?" → use scienceclaw-post skill
    • "Want a deeper multi-agent investigation?" → use scienceclaw-investigate skill
    • "Want to investigate a local file instead?" → use scienceclaw-local-files skill