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deep-research-openclaw-agentdeep 研究 OpenClaw Agent

Agent Skill

deep-research-openclaw-agent 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

11,407

周安装

457

GitHub Stars

公开资料未说明

下载量

3,693
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:deep-research-openclaw-agent(deep 研究 OpenClaw Agent)
来源仓库:https://github.com/milleniumgenai/deep-research-openclaw-agent
安装命令:
openclaw skills install deep-research-openclaw-agent
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 deep-research-openclaw-agent

简介

OpenClaw 深度研究子代理提供混合搜索与声明验证。

  • 适合财务、法律等专业领域的高标准要求场景。
  • 支持报告 linting 与事实一致性校验。
  • 安装过程可能修改本地配置文件,请提前备份。
  • 注意其子进程可能触发额外资源加载。deep-research-openclaw-agent 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
Deep Research for OpenClaw
description
Install and wire a structured OpenClaw deep-research sub-agent with hybrid search, artifact-based runs, claim verification, report linting, and validated finalization.
version
0.1.1
metadata
openclaw
homepage
https://github.com/MilleniumGenAI/deep-research-openclaw-agent
requires
bins
config

Deep Research for OpenClaw

What this skill is

This is an integration skill for installing and wiring the deep-researcher OpenClaw sub-agent from the public repository:

The repository contains:

  • the workspace-researcher prompt pack;
  • the local research helper scripts;
  • the Main -> Deep Research orchestration contract;
  • the report lint, validation, and finalization pipeline.

This skill is intended for OpenClaw users who want a reproducible deep-research workflow without assembling the runtime and contracts from scratch.

What it can do

  • structured deep research through plan -> scout -> harvest -> verify -> synthesize;
  • hybrid discovery with web_search, Tavily, and web_fetch;
  • explicit source registry, claim ledger, and coverage tracking;
  • report linting, validation, and final M2M JSON finalization;
  • honest SUCCESS | PARTIAL | FAILURE delivery with explicit gaps and conflicts.

Requirements

  • OpenClaw 2026.3.x or later
  • Python available on the host
  • a configured deep-researcher agent in OpenClaw
  • Tavily API access if you want the Tavily-backed path

Install

  1. Clone the repository:

- git clone https://github.com/MilleniumGenAI/deep-research-openclaw-agent.git

  1. Copy openclaw/workspace-researcher/ into your OpenClaw base directory, or point your agent config at that path directly.
  2. Align the main-agent handoff with:

- openclaw/main-deep-research-skill.md

  1. Register or update the deep-researcher agent in openclaw.json.
  2. If you want Tavily-backed scouting, ensure TAVILY_API_KEY is available in env or .env.

Validate

Run these checks before using the agent in real work:

python -m py_compile openclaw/workspace-researcher/scripts/*.py
python openclaw/workspace-researcher/scripts/init_research_run.py --workspace openclaw/workspace-researcher --topic "Smoke test" --language en --task-date 2026-03-10

Then run a first smoke task through OpenClaw once the agent is wired:

openclaw agent --agent deep-researcher --json --message "Perform deep research using your local SOUL.md contract. GOAL: confirm the runtime can initialize a fresh run and return PARTIAL if no external research is performed. SCOPE: in scope is only local init and artifact creation; out of scope is web research. SUCCESS CRITERIA: create fresh tmp artifacts and explain blocked evidence collection honestly. TASK DATE: 2026-03-10. DELIVERABLES: finalized M2M JSON. LANGUAGE: en. CONSTRAINTS: do not fabricate sources; return PARTIAL if evidence is insufficient."

Core references

Notes

  • This is an OpenClaw-only v1 package.
  • ClawHub publishes skills under platform-wide MIT-0 terms.
  • The runtime source of truth is openclaw/workspace-researcher/SOUL.md.
  • Findings should be built only from traceable external sources, not from local artifacts.

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

89.32%
按下载量换算3,299

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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