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solo-research单独研究

Agent Skill

solo-research 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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

964

周安装

41

GitHub Stars

15

下载量

338
CodexClaudeCursorGemini CLI

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

unknown

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-research(单独研究)
来源仓库:https://github.com/fortunto2/solo-factory
仓库路径:skills/solo-research
安装命令:
npx skills add https://github.com/fortunto2/solo-factory --skill solo-research
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/fortunto2/solo-factory --skill solo-research

简介

solo-research 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于独立研究项目相关的信息检索任务。
  • 可通过 GitHub 仓库和 README 文档核验具体功能和使用方法。
  • 安装前应确认权限、维护状态及是否涉及网络或文件操作。
  • 建议结合研究主题验证其信息覆盖范围。

SKILL.md

/research

Deep research before PRD generation. Produces a structured research.md with competitive analysis, user pain points, SEO/ASO keywords, naming/domain options, and market sizing.

Live Context

  • Branch:!git branch --show-current 2>/dev/null
  • Recent changes:!git log --oneline -5 2>/dev/null

MCP Tools (use if available)

If MCP tools are available, prefer them over CLI:

  • kb_search(query, n_results) — search knowledge base for related docs
  • web_search(query, engines, include_raw_content) — web search with engine routing
  • session_search(query, project) — find how similar research was done before
  • project_info(name) — check project details and stacks
  • codegraph_explain(project) — architecture overview of an existing project (stack, patterns, deps)
  • codegraph_query(query) — raw Cypher queries against code graph (find shared packages, dependencies)
  • project_code_search(query, project) — semantic search over project source code

MCP web_search supports engine override: engines="reddit", engines="youtube", etc. If MCP tools are not available, use WebSearch/WebFetch as primary. If MCP web_search tool is available, use it for better results.

Reddit Search Best Practices

  • Max 3 keywords in reddit queries — more keywords = fewer results
  • Good: "product hunt outreach launch" — Bad: "product hunt scraper maker profiles linkedin outreach launch strategy"
  • include_raw_content=true rarely works for Reddit — use fallback chain below

Reddit Content Access — Fallback Chain

When a search finds a relevant Reddit post, reading its full content requires a fallback chain:

1. MCP Playwright (old.reddit.com)     ← BEST: bypasses CAPTCHA, full post + comments
2. PullPush API (api.pullpush.io)      ← search by query/subreddit/author/score/date
3. MCP web_search include_raw_content   ← sometimes works, often truncated
4. WebFetch / WebSearch snippets        ← last resort, partial data only

Method 1: MCP Playwright (recommended for full post content)

  • Use browser_navigate("https://old.reddit.com/r/...") — old.reddit.com loads without CAPTCHA
  • www.reddit.com shows CAPTCHA ("Prove your humanity"), always use old.reddit.com
  • Snapshot contains full post text + comments in structured YAML
  • Example: old.reddit.com/r/indiehackers/comments/abc123/post_title/

Method 2: PullPush API (for search/discovery)

  • Endpoint: https://api.pullpush.io/reddit/submission/search
  • Params: q, subreddit, author, score (e.g. >10,<100), since/until (unix timestamps), size (max 100)
  • Rate limits: soft 15 req/min, hard 30 req/min, 1000 req/hr. Sleep 4 sec between requests.
  • Returns JSON with full selftext, author, score, created_utc
  • Comment search: /reddit/comment/search (same params)
  • Can use via curl:
curl -s "https://api.pullpush.io/reddit/submission/search?q=product+hunt+launch&subreddit=indiehackers&size=10"

Method 3: Reddit.json endpoint (often blocked)

  • Append .json to any Reddit URL: reddit.com/r/sub/comments/id.json
  • Returns raw JSON with full post + comments
  • Frequently blocked (403/429) — use as opportunistic fallback only

Method 4: PRAW (Reddit Official API, for live search/user profiles)

  • praw-dev/praw — Python Reddit API Wrapper
  • OAuth2 auth, built-in rate limiting, sync/async support
  • Best for: live subreddit search, user profiles, comment trees
  • pip install praw / uv add praw

Search Strategy: Hybrid (MCP + WebSearch)

Use multiple search backends together. Each has strengths:

StepBest backendWhy
CompetitorsWebSearch + site:producthunt.com + site:g2.comBroad discovery + Product Hunt + B2B reviews
Reddit / Pain pointsMCP web_search with engines: reddit (max 3 keywords!) + MCP Playwright for full postsPullPush API, selftext in content
YouTube reviewsMCP web_search with engines: youtubeVideo reviews (views = demand)
Market sizeWebSearchSynthesizes numbers from 10 sources
SEO / ASOWebSearchBroader coverage, trend data
Page scrapingWebFetch or MCP web_search with include_raw_contentUp to 5000 chars of page content
Hacker NewsWebSearch site:news.ycombinator.comHN discussions and opinions
Funding / CompaniesWebSearch site:crunchbase.comCompetitor funding, team size
Verified revenueWebFetch trustmrr.com/startup/<slug>Stripe-verified MRR, growth, tech stack, traffic

Search Availability

Use WebSearch/WebFetch as primary. If MCP web_search tool is available, use it for better results (supports engine routing and raw content extraction).

Steps

  1. Parse the idea from $ARGUMENTS. If empty, ask the user what idea they want to research.
  2. Detect product type — infer from the idea description:

- Keywords like "app", "mobile", "iPhone", "Android" → mobile (ios/android) - Keywords like "website", "SaaS", "dashboard", "web app" → web - Keywords like "CLI", "terminal", "command line" → cli - Keywords like "API", "backend", "service" → api - Keywords like "extension", "plugin", "browser" → web (extension) - Default if unclear → web - Only ask via AskUserQuestion if truly ambiguous (e.g., "build a todo app" could be web or mobile) - This determines which research sections apply (ASO for mobile, SEO for web, etc.)

  1. Search knowledge base and past work:

- If MCP kb_search available: kb_search(query="<idea keywords>", n_results=5) - If MCP session_search available: session_search(query="<idea keywords>") — check if this idea was researched before - Otherwise: Grep for keywords in .md files - Check if research.md or prd.md already exist for this idea.

  1. Check existing portfolio (if MCP codegraph tools available):

- codegraph_explain(project="<similar project>") — architecture overview of related projects in the portfolio - project_code_search(query="<relevant pattern>", project="<sibling>") — find reusable code, patterns, infrastructure - codegraph_query("MATCH (p:Project)-[:DEPENDS_ON]->(pkg:Package) WHERE pkg.name CONTAINS '<relevant tech>' RETURN p.name, pkg.name") — find projects using similar tech - This helps assess: feasibility, reusable code, stack decisions, and time estimates - If no MCP tools available, skip this step.

  1. Competitive analysis — use WebSearch (primary) + MCP web_search (if available):

- "<idea> competitors alternatives 2026" — broad discovery - "<idea> app review pricing" — pricing data - WebFetch or MCP include_raw_content=true: scrape competitor URLs for detailed pricing - MCP engines: reddit or WebSearch: "<idea> vs" — user opinions - "site:producthunt.com <idea>" — Product Hunt launches - "site:g2.com <idea>" or "site:capterra.com <idea>" — B2B reviews - "site:crunchbase.com <competitor>" — funding, team size - "site:trustmrr.com <idea>" or WebFetch trustmrr.com/startup/<slug> — Stripe-verified MRR, growth %, tech stack, traffic (24h/7d/30d) - For each competitor extract: name, URL, pricing, key features, weaknesses, verified MRR (if on TrustMRR)

  1. User pain points — use MCP web_search / WebSearch + YouTube:

- MCP engines: reddit or WebSearch: "<problem>" — Reddit discussions (max 3 keywords!) - If Reddit post found but content not available → open via MCP Playwright: browser_navigate("https://old.reddit.com/r/...") — old.reddit.com bypasses CAPTCHA - MCP engines: youtube or WebSearch: "<problem> review" — video reviews - "site:news.ycombinator.com <problem>" — Hacker News opinions - WebSearch: "<problem> frustrating OR annoying" — broader sweep - Synthesis: top 5 pain points with quotes and source URLs

  1. SEO / ASO analysis (depends on product type from step 2): For web apps: For mobile apps:

- "<competitor> SEO keywords ranking" — competitor keywords - "<problem domain> search volume trends 2026" — demand signals - WebFetch or MCP include_raw_content: scrape competitor pages for meta tags - Result: keyword table (keyword, intent, competition, relevance) - "<category> App Store top apps keywords 2026" — category landscape - "site:reddit.com <competitor app> review" — user complaints - Result: ASO keywords, competitor ratings, common complaints

  1. Naming, domains, and company registration: See references/domain-check.md (bundled with this skill) for TLD priority tiers, bash scripts, gotchas, and trademark check methods.

- Generate 7-10 name candidates (mix of descriptive + invented/brandable) - Domain availability: triple verification (whois → dig → RDAP) - Trademark + company name conflict checks

  1. User Personas (2-3 quick personas from research data): Based on pain points (step 6) and competitive gaps (step 5), generate 2-3 lightweight personas: Field Example Name "Alex, freelance designer" Segment Early-career freelancers, $3-8K/mo JTBD "When I finish a project, I want to send a professional invoice in under 60 seconds so I can get paid faster" Pain Top pain point from step 6 with source quote Current solution What they use today (competitor or workaround) Switching trigger What would make them try something new Keep personas grounded in evidence from steps 5-6. No fictional demographics — only what the data supports. These feed directly into /validate for ICP and PRD generation.
  2. Interview Script (optional, if user plans customer interviews):

Generate a 7-question JTBD interview script based on the personas above:

  1. Context: "Tell me about the last time you [core action]..." (open-ended, past tense)
  2. Trigger: "What prompted you to look for a solution?" (switching moment)
  3. Current workflow: "Walk me through how you do this today, step by step"
  4. Pain: "What's the most frustrating part?" (don't lead — let them name it)
  5. Alternatives tried: "What else have you tried? What happened?"
  6. Outcome: "What would 'solved' look like for you?"
  7. Willingness to pay: "If something did exactly that, what would it be worth to you?"

Rules: past tense only (what they DID, not what they WOULD do), no leading questions, no feature pitching. Reference: JTBD interview methodology (Bob Moesta).

Write to docs/interview-script.md if generated.

  1. Market sizing (TAM/SAM/SOM) — use WebSearch (primary):
  • WebSearch: "<market> market size 2025 2026 report" — synthesizes numbers
  • WebSearch: "<market> growth rate CAGR billion" — growth projections
  • Extrapolation: TAM → SAM → SOM (Year 1)
  1. Write research.md — write to docs/research.md in the current project directory. Create the directory if needed.
  2. Output summary:

- Key findings (3-5 bullets) - Recommendation: GO / NO-GO / PIVOT with brief reasoning - Path to generated research.md - Suggested next step: /validate <idea>

research.md Format

See references/research-template.md (bundled with this skill) for the full output template (frontmatter, 6 sections, tables).

Notes

  • Always use kebab-case for project directory names
  • If research.md already exists, ask before overwriting
  • Run search queries in parallel when independent

Common Issues

MCP web_search not available

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

Domain check returns wrong results

Cause: .app/.dev whois shows TLD creation date for unregistered domains. Fix: Use the triple verification method (whois -> dig -> RDAP). Check Name Server and Registrar fields, not creation date.

research.md already exists

Cause: Previous research run for this idea. Fix: Skill asks before overwriting. Choose to merge new findings or start fresh.

Proactive Search Practices

Reddit Deep Dive

  1. MCP web_search or WebSearch — use for discovery (max 3 keywords for Reddit), get post URLs
  2. MCP Playwright — open old.reddit.com URLs to read full post + comments (bypasses CAPTCHA)
  3. Extract quotes — copy key phrases with attribution (u/username, subreddit, date)
  4. Cross-post detection — same post in multiple subreddits = higher signal

Product Hunt Research

  1. producthunt.com/visit-streaks — streak leaderboard (scrapeable via Playwright)
  2. producthunt.com/@username — profile with social links, maker history, points
  3. PH API v2 is broken — redacts usernames/Twitter since Feb 2023, use scraping
  4. Apify actors — check for DEPRECATED status before relying on them (mass deprecation Sep 2025)

TrustMRR Revenue Validation

  1. trustmrr.com/startup/<slug> — Stripe-verified MRR, growth %, subscriptions, traffic
  2. WebFetch works — no auth needed, returns full page with JSON-LD structured data
  3. Data fields: MRR, all-time revenue, last 30 days, active subs, tech stack, traffic (24h/7d/30d), category, founder X handle
  4. Use for: competitor revenue validation, market sizing with real data, tech stack discovery
  5. Search: "site:trustmrr.com <category or idea>" to find similar startups with verified revenue
  6. Apify scrapers: TrustMRR Scraper for bulk extraction

GitHub Library Discovery

  1. MCP engines: github — often returns empty, use WebSearch as primary
  2. github.com/topics/ — browse topic pages via Playwright or WebFetch
  3. Check stars, last update, open issues — avoid abandoned repos

Blocked Content Fallback Chain

MCP Playwright (best) → PullPush API (Reddit) → WebFetch → WebSearch snippets → MCP web_search include_raw_content

If a page returns 403/CAPTCHA via WebFetch:

  1. Reddit: MCP Playwright → old.reddit.com (always works, no CAPTCHA)
  2. Reddit search: PullPush API api.pullpush.io (structured JSON, full selftext)
  3. Product Hunt / other sites: MCP Playwright browser_navigate (no captcha on most sites)
  4. General: WebSearch snippets + WebSearch synthesis

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

36.75%
按下载量换算124

Claude

28.95%
按下载量换算98

Cursor

17.02%
按下载量换算58

Gemini CLI

9.36%
按下载量换算32

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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