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solo-community-outreach单独社区外展

Agent Skill

solo-community-outreach 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

21,976

周安装

889

GitHub Stars

公开资料未说明

下载量

6,899
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-community-outreach(单独社区外展)
来源仓库:https://github.com/fortunto2/solo-community-outreach
安装命令:
openclaw skills install solo-community-outreach
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-community-outreach

简介

查找 Reddit、HN 和 ProductHunt 相关话题并起草社区回复草稿。

  • 基于价值优先原则生成高互动潜力文案模板。solo-community-outreach 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 支持关键词过滤与情感倾向调整以适应不同平台调性。
  • 输出内容为建议框架,实际发布需人工润色与合规审核。
  • 避免直接复制粘贴,强调原创性与用户共鸣点。

SKILL.md

name
solo-community-outreach
description
Find relevant Reddit, HN, and ProductHunt threads and draft value-first community responses with launch checklist. Use when user says "find communities", "draft outreach", "Reddit promotion", "ProductHunt launch", or "community marketing". Do NOT use for social media posts (use /content-gen) or video scripts (use /video-promo).
license
MIT
metadata
author
fortunto2
version
1.1.1
openclaw
emoji
💬
allowed-tools
Read, Grep, Glob, Write, WebSearch, WebFetch, AskUserQuestion, mcp__solograph__web_search, mcp__solograph__kb_search, mcp__solograph__project_info
argument-hint
<project-name or idea>

/community-outreach

Find relevant community threads (Reddit, Hacker News, ProductHunt) and draft contextual, value-first responses. NOT spam — genuine helpful answers that naturally mention the product.

MCP Tools (use if available)

  • web_search(query, engines, include_raw_content) — search Reddit, HN, web
  • kb_search(query) — find related methodology
  • project_info(name) — get project details

If MCP tools are not available, use WebSearch/WebFetch as fallback.

Steps

  1. Parse project from $ARGUMENTS.

- Read PRD/README to understand: problem, solution, ICP, key features. - If empty: ask via AskUserQuestion.

  1. Extract search keywords:

- Problem keywords (what users complain about) - Solution keywords (what users search for) - Category keywords (the market/niche) - Competitor names (for "vs" and "alternative" threads)

  1. Search communities (run searches in parallel):

### 3a. Reddit For each keyword group, search via MCP web_search(query) or WebSearch: - "{problem} reddit" — pain point threads - "{solution category} recommendations reddit" — recommendation requests - "{competitor} alternative reddit" — competitor frustration - "{competitor} vs reddit" — comparison threads

For each result, extract: subreddit, title, URL, post date, comment count. Filter: prefer threads < 6 months old, > 5 comments (active).

### 3b. Hacker News Search via site:news.ycombinator.com: - "Show HN: {similar product category}" — similar launches - "Ask HN: {problem domain}" — questions in the space - "{competitor name} site:news.ycombinator.com" — competitor mentions

Extract: title, URL, points, comment count.

### 3c. ProductHunt Search via site:producthunt.com: - "{product category} site:producthunt.com" — similar launches - "{competitor} site:producthunt.com" — competitor pages

Extract: product names, launch dates, upvote counts, taglines.

### 3d. Other Communities (optional) - site:indiehackers.com "{problem}" — Indie Hackers - site:dev.to "{solution category}" — Dev.to (if technical product)

  1. Forced reasoning — outreach strategy:

Before drafting, write out: - Best 5 threads to engage with (highest relevance + activity) - Tone per community: Reddit (casual, self-deprecating), HN (technical, data-driven), PH (enthusiastic, builder) - Value-first angle: What genuine help can we offer BEFORE mentioning the product? - Red lines: No astroturfing, no fake accounts, always disclose you're the builder

  1. Draft responses for top 5 threads:

For each thread:

   ### Thread: {title}
   **URL:** {url}
   **Subreddit/Community:** {community}
   **Why relevant:** {1 sentence}

   **Draft response:**
   {2-4 paragraph response that:
   - Directly addresses the question/problem
   - Provides genuine value (tips, experience, data)
   - Mentions the product naturally (last paragraph)
   - Includes "disclaimer: I'm the developer" for transparency
   }
  1. Generate ProductHunt launch checklist:
   ## ProductHunt Launch Checklist

   ### Pre-Launch (1 week before)
   - [ ] Hunter identified (or self-hunting)
   - [ ] Tagline ready (< 60 chars): "{tagline}"
   - [ ] Description ready (< 260 chars)
   - [ ] 5+ screenshots/GIF prepared
   - [ ] Maker comment drafted (story + problem + solution)
   - [ ] Launch day scheduled (Tuesday-Thursday, 00:01 PST)

   ### Launch Day
   - [ ] Post live and verified
   - [ ] Maker comment posted immediately
   - [ ] Share in relevant communities (not vote-begging)
   - [ ] Respond to all comments within 1 hour
   - [ ] Share progress on Twitter/LinkedIn

   ### Post-Launch
   - [ ] Thank supporters
   - [ ] Collect feedback from comments
   - [ ] Update product based on feedback
  1. Write outreach plan to docs/outreach-plan.md:
   # Community Outreach Plan: {Project Name}

   **Generated:** {YYYY-MM-DD}
   **Product:** {one-line description}
   **ICP:** {target persona}

   ## Target Communities

   | Community | Relevant Threads Found | Priority |
   |-----------|----------------------|----------|
   | r/{subreddit} | N | high/medium/low |
   | Hacker News | N | high/medium/low |
   | ProductHunt | N | high/medium/low |

   ## Top Threads to Engage

   {5 thread drafts from step 5}

   ## ProductHunt Launch Checklist

   {checklist from step 6}

   ## Search Keywords Used
   - {keyword1}: N results
   - {keyword2}: N results

   ---
   *Generated by /community-outreach. Review all drafts before posting.*
  1. Output summary — communities found, top 3 threads to engage, PH readiness.

Critical Rules

  1. Value first, product second — every response must genuinely help the person
  2. Always disclose — "I'm the developer" or "disclaimer: I built this"
  3. No vote manipulation — never ask for upvotes
  4. No astroturfing — never pretend to be a user
  5. Respect community rules — check subreddit rules before posting
  6. Quality over quantity — 5 great responses > 50 generic ones

Common Issues

Web search not available

Cause: MCP web_search tool not configured or WebSearch not accessible. Fix: Use WebSearch/WebFetch as primary. For better results with engine routing (Reddit, HN), set up SearXNG (private, self-hosted, free) and configure solograph MCP.

No relevant threads found

Cause: Niche too small or wrong keywords. Fix: Broaden search terms. Try competitor names, problem descriptions, or adjacent categories.

Responses sound promotional

Cause: Product mention too prominent or lacks genuine value. Fix: Rewrite with value-first approach: 80% helpful answer, 20% product mention. Always include builder disclosure.

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

79.68%
按下载量换算5,497

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。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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