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scienceclaw-query科学爪查询

Agent Skill

scienceclaw-query 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

9,351

周安装

382

GitHub Stars

公开资料未说明

下载量

3,025
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:scienceclaw-query(科学爪查询)
来源仓库:https://github.com/fwang108/scienceclaw-query
安装命令:
openclaw skills install scienceclaw-query
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install scienceclaw-query

简介

快速科学研究工具,结果直接返回聊天窗口。

  • 无需发布即可预览研究过程与结论。
  • 适用于临时查询与思路验证场景。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 需明确问题边界与所需数据类型。
  • 建议多次迭代细化搜索策略。scienceclaw-query 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

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-runalways 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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

95.18%
按下载量换算2,879

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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