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solo-swarm单独集群

Agent Skill

solo-swarm 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

21,348

周安装

917

GitHub Stars

公开资料未说明

下载量

7,483
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:solo-swarm(单独集群)
来源仓库:https://github.com/fortunto2/solo-swarm
安装命令:
openclaw skills install solo-swarm
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 solo-swarm

简介

启动三个并行代理分别从市场、用户与技术角度研究想法。

  • 聚合多方视角输出综合评估报告减少认知盲区。
  • 支持自定义代理角色与提问模板灵活适配场景。
  • 并发执行可能增加资源消耗需控制频率。solo-swarm 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 结果整合由主控 Agent 完成避免信息碎片化。

SKILL.md

name
solo-swarm
description
Launch 3 parallel research agents (market, users, tech) to investigate an idea from multiple angles simultaneously. Use when user says "swarm research", "parallel research", "investigate fast", "3 agents", "team research", or wants faster alternative to /research. Produces research.md. Do NOT use for solo research (use /research) or idea scoring (use /validate).
license
MIT
metadata
author
fortunto2
version
1.6.0
openclaw
emoji
🐝
allowed-tools
Read, Grep, Glob, Bash, WebSearch, WebFetch, Write, mcp__solograph__web_search, mcp__solograph__kb_search, mcp__solograph__project_info, mcp__solograph__codegraph_query, mcp__solograph__codegraph_explain, mcp__solograph__project_code_search, mcp__solograph__session_search
argument-hint
[idea name or description]

/swarm

Create an agent team to research "$ARGUMENTS" from multiple perspectives in parallel.

Team Structure

Spawn 3 teammates, each with a distinct research focus:

1. Market Researcher

Focus: competitors, market size, pricing models, business models.

  • Search for direct and indirect competitors
  • Find market reports with TAM/SAM/SOM figures
  • Analyze pricing strategies and monetization
  • Identify market gaps and opportunities
  • Check Product Hunt, G2, Capterra for existing products

2. User Researcher

Focus: pain points, user sentiment, feature requests.

  • Search Reddit for user discussions (site:reddit.com <query> via WebSearch, or MCP web_search if available)
  • Search Hacker News for tech community opinions (site:news.ycombinator.com)
  • If MCP session_search available: check if this idea was researched before in past sessions
  • Find app reviews and ratings
  • Extract direct user quotes about frustrations
  • Identify unmet needs and feature requests

3. Technical Analyst

Focus: feasibility, tech stack, existing solutions, implementation complexity.

  • Search GitHub for open-source alternatives (site:github.com <query>)
  • Evaluate tech stack options
  • If MCP project_info available: check existing projects for reusable code
  • If MCP codegraph_explain available: get architecture overview of similar existing projects
  • If MCP codegraph_query available: find shared packages across projects
  • If MCP project_code_search available: search for reusable patterns, services, infrastructure across existing projects
  • Assess implementation complexity and timeline

Search Backends

Teammates should use available search tools:

  • WebSearch (built-in) — broad discovery, market reports, always available
  • WebFetch — scrape specific URLs for details, always available
  • MCP web_search (if available) — additional search with engine routing
  • MCP kb_search (if available) — search local knowledge base for related research

Domain filtering: use site:github.com, site:reddit.com etc. for targeted results.

Coordination

  • Each teammate writes findings to a shared task list
  • Require plan approval before teammates start deep research
  • After all complete, synthesize findings into research.md
  • Use the research.md format from /research skill

Output

After team completes, the lead should:

  1. Synthesize findings from all 3 teammates
  2. Write research.md to docs/ in the current project directory
  3. Provide GO / NO-GO / PIVOT recommendation
  4. Suggest next step: /validate <idea>

Common Issues

Agent team not available

Cause: CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS env var not set. Fix: Ensure .claude/settings.json has "env": {"CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1"}.

Teammates produce overlapping findings

Cause: Research areas not clearly separated. Fix: Each teammate has a distinct focus (market/users/tech). The lead synthesizes and deduplicates findings.

Web search returns limited results

Cause: No additional search backends configured. Fix: Teammates fall back to WebSearch (built-in) which is always available. For richer results with engine routing (Reddit, GitHub, YouTube), set up SearXNG (private, self-hosted, free) and configure solograph MCP.

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

90.46%
按下载量换算6,769

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install solo-swarm 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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