solo-research

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Original

English

🇨🇳

Translation

Chinese

/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.

在生成PRD之前进行深度调研。生成结构清晰的

research.md

文件，包含竞品分析、用户痛点、SEO/ASO关键词、命名/域名选项以及市场规模测算内容。

MCP Tools (use if available)

MCP工具（如有可用请使用）

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.

如果MCP工具可用，优先于CLI使用：

```
kb_search(query, n_results)
```
— 在知识库中搜索相关文档

web_search(query, engines, include_raw_content)

— 支持引擎路由的网页搜索

```
session_search(query, project)
```
— 查找此前类似调研的执行方式
```
project_info(name)
```
— 查看项目详情与技术栈
```
codegraph_explain(project)
```
— 现有项目的架构概述（技术栈、模式、依赖）
```
codegraph_query(query)
```
— 针对代码图谱的原生Cypher查询（查找共享包、依赖关系）
```
project_code_search(query, project)
```
— 对项目源代码进行语义搜索

MCP

web_search

支持引擎覆盖：

engines="reddit"

、

engines="youtube"

等。如果MCP工具不可用，以WebSearch/WebFetch作为主要工具。若MCP web_search工具可用，使用它可获得更优结果。

Reddit Search Best Practices

Reddit搜索最佳实践

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查询中最多使用3个关键词 — 关键词越多，结果越少

示例：有效：

"product hunt outreach launch"

— 无效：

"product hunt scraper maker profiles linkedin outreach launch strategy"

```
include_raw_content=true
```
在Reddit上很少生效 — 使用下方的回退流程

Reddit Content Access — Fallback Chain

Reddit内容获取 — 回退流程

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:

bash

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
```

当搜索找到相关Reddit帖子时，读取完整内容需要遵循以下回退流程：

1. MCP Playwright (old.reddit.com)     ← 最佳选择：绕过验证码，获取完整帖子+评论
2. PullPush API (api.pullpush.io)      ← 按查询/子版块/作者/评分/日期搜索
3. MCP web_search include_raw_content   ← 偶尔生效，结果常被截断
4. WebFetch / WebSearch 片段        ← 最后手段：仅能获取部分数据

方法1：MCP Playwright（推荐用于获取完整帖子内容）

使用
```
browser_navigate("https://old.reddit.com/r/...")
```
— old.reddit.com无需验证码即可加载
```
www.reddit.com
```
会显示验证码（“验证您的身份”），请始终使用
```
old.reddit.com
```
快照包含结构化YAML格式的完整帖子文本+评论

示例：

old.reddit.com/r/indiehackers/comments/abc123/post_title/

方法2：PullPush API（用于搜索/发现）

端点：

https://api.pullpush.io/reddit/submission/search

参数：
```
q
```
、
```
subreddit
```
、
```
author
```
、
```
score
```
（例如
```
>10,<100
```
）、
```
since
```
/
```
until
```
（Unix时间戳）、
```
size
```
（最大100）
速率限制：软限制15请求/分钟，硬限制30请求/分钟，1000请求/小时。请求间隔至少4秒。
返回包含完整
```
selftext
```
、作者、评分、created_utc的JSON数据
评论搜索：
```
/reddit/comment/search
```
（参数相同）
可通过curl调用：

bash

curl -s "https://api.pullpush.io/reddit/submission/search?q=product+hunt+launch&subreddit=indiehackers&size=10"

方法3：Reddit .json端点（常被屏蔽）

在任意Reddit URL后追加
```
.json
```
：
```
reddit.com/r/sub/comments/id.json
```
返回包含完整帖子+评论的原生JSON数据
经常被屏蔽（403/429） — 仅作为机会性回退方案

方法4：PRAW（Reddit官方API，用于实时搜索/用户资料）

praw-dev/praw — Python Reddit API封装
支持OAuth2认证、内置速率限制、同步/异步调用
最佳适用场景：实时子版块搜索、用户资料、评论树
安装方式：
```
pip install praw
```
/
```
uv add praw
```

Search Strategy: Hybrid (MCP + WebSearch)

搜索策略：混合模式（MCP + WebSearch）

Use multiple search backends together. Each has strengths:

Step	Best backend	Why
Competitors	WebSearch + `site:producthunt.com` + `site:g2.com`	Broad discovery + Product Hunt + B2B reviews
Reddit / Pain points	MCP `web_search` with `engines: reddit` (max 3 keywords!) + MCP Playwright for full posts	PullPush API, selftext in content
YouTube reviews	MCP `web_search` with `engines: youtube`	Video reviews (views = demand)
Market size	WebSearch	Synthesizes numbers from 10 sources
SEO / ASO	WebSearch	Broader coverage, trend data
Page scraping	WebFetch or MCP `web_search` with `include_raw_content`	Up to 5000 chars of page content
Hacker News	WebSearch `site:news.ycombinator.com`	HN discussions and opinions
Funding / Companies	WebSearch `site:crunchbase.com`	Competitor funding, team size
Verified revenue	WebFetch `trustmrr.com/startup/<slug>`	Stripe-verified MRR, growth, tech stack, traffic

结合使用多种搜索后端，各后端有其优势：

步骤	最佳后端	原因
竞品调研	WebSearch + `site:producthunt.com` + `site:g2.com`	广泛发现竞品 + Product Hunt + B2B评测
Reddit / 用户痛点	MCP `web_search` （指定 `engines: reddit` ，最多3个关键词！） + MCP Playwright获取完整帖子	PullPush API可获取帖子正文
YouTube评测	MCP `web_search` （指定 `engines: youtube` ）	视频评测（播放量=需求信号）
市场规模	WebSearch	综合10个数据源的统计数据
SEO / ASO	WebSearch	覆盖范围更广，包含趋势数据
页面爬取	WebFetch 或 MCP `web_search` （开启 `include_raw_content` ）	最多可获取5000字符的页面内容
Hacker News	WebSearch `site:news.ycombinator.com`	获取HN社区的讨论与观点
融资 / 企业信息	WebSearch `site:crunchbase.com`	竞品融资情况、团队规模
已验证收入	WebFetch `trustmrr.com/startup/<slug>`	Stripe验证的MRR、增长数据、技术栈、流量

Search Availability

搜索工具可用性

Use WebSearch/WebFetch as primary. If MCP

web_search

tool is available, use it for better results (supports engine routing and raw content extraction).

以WebSearch/WebFetch作为主要工具。若MCP

web_search

工具可用，使用它可获得更优结果（支持引擎路由与原始内容提取）。

Steps

执行步骤

Parse the idea from
```
$ARGUMENTS
```
. If empty, ask the user what idea they want to research.
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.)
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.
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.
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)
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
SEO / ASO analysis (depends on product type from step 2):

For web 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)
For mobile apps:
- ```
"<category> App Store top apps keywords 2026"
```
  — category landscape
- ```
"site:reddit.com <competitor app> review"
```
  — user complaints
- Result: ASO keywords, competitor ratings, common complaints
Naming, domains, and company registration:
- Generate 7-10 name candidates (mix of descriptive + invented/brandable)
- Domain availability: triple verification (whois → dig → RDAP)
- Trademark + company name conflict checks
See
```
references/domain-check.md
```
(bundled with this skill) for TLD priority tiers, bash scripts, gotchas, and trademark check methods.
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)
Write
research.md
— write to
```
docs/research.md
```
in the current project directory. Create the directory if needed.
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>
```

解析创意：从
```
$ARGUMENTS
```
中解析用户的创意。若参数为空，询问用户需要调研的创意内容。
识别产品类型：从创意描述中推断：
- 包含“app”“mobile”“iPhone”“Android”等关键词 → 移动应用（ios/android）
- 包含“website”“SaaS”“dashboard”“web app”等关键词 → 网页应用
- 包含“CLI”“terminal”“command line”等关键词 → 命令行工具
- 包含“API”“backend”“service”等关键词 → 后端服务
- 包含“extension”“plugin”“browser”等关键词 → 网页应用（扩展程序）
- 若无法明确判断，默认归类为网页应用
- 仅当存在真正歧义时才询问用户（例如“构建待办应用”可能是网页或移动应用）
- 产品类型将决定适用的调研模块（移动应用用ASO，网页应用用SEO等）
搜索知识库与过往成果：
- 若MCP
```
kb_search
```
  可用：
```
kb_search(query="<创意关键词>", n_results=5)
```
- 若MCP
```
session_search
```
  可用：
```
session_search(query="<创意关键词>")
```
  — 检查该创意是否已被调研过
- 若以上工具不可用：在
```
.md
```
  文件中搜索关键词
- 检查当前创意是否已存在
```
research.md
```
  或
```
prd.md
```
  文件
检查现有项目组合（若MCP codegraph工具可用）：
- ```
codegraph_explain(project="<类似项目>")
```
  — 获取项目组合中相关项目的架构概述
- ```
project_code_search(query="<相关模式>", project="<关联项目>")
```
  — 查找可复用代码、模式、基础设施
- ```
codegraph_query("MATCH (p:Project)-[:DEPENDS_ON]->(pkg:Package) WHERE pkg.name CONTAINS '<相关技术>' RETURN p.name, pkg.name")
```
  — 查找使用类似技术的项目
- 此步骤有助于评估：可行性、可复用代码、技术栈决策、时间预估
- 若MCP工具不可用，跳过此步骤
竞品分析 — 使用WebSearch（主要） + MCP web_search（如有可用）：
- 搜索词：
```
"<创意> competitors alternatives 2026"
```
  — 广泛发现竞品
- 搜索词：
```
"<创意> app review pricing"
```
  — 获取定价数据
- 使用WebFetch或MCP
```
include_raw_content=true
```
  ：爬取竞品URL获取详细定价
- 使用MCP
```
engines: reddit
```
  或WebSearch：
```
"<创意> vs"
```
  — 获取用户观点
- 搜索词：
```
"site:producthunt.com <创意>"
```
  — 查看Product Hunt上的竞品发布情况
- 搜索词：
```
"site:g2.com <创意>"
```
  或
```
"site:capterra.com <创意>"
```
  — 获取B2B评测
- 搜索词：
```
"site:crunchbase.com <竞品名称>"
```
  — 获取竞品融资、团队规模
- 搜索词：
```
"site:trustmrr.com <创意>"
```
  或 WebFetch
```
trustmrr.com/startup/<slug>
```
  — 获取Stripe验证的MRR、增长率、技术栈、流量（24h/7d/30d）
- 为每个竞品提取：名称、URL、定价、核心功能、劣势、已验证MRR（若在TrustMRR上有数据）
用户痛点调研 — 使用MCP web_search / WebSearch + YouTube：
- 使用MCP
```
engines: reddit
```
  或WebSearch：
```
"<问题>"
```
  — 查找Reddit讨论（最多3个关键词！）
- 若找到Reddit帖子但无法获取内容 → 使用MCP Playwright打开：
```
browser_navigate("https://old.reddit.com/r/...")
```
  — old.reddit.com可绕过验证码
- 使用MCP
```
engines: youtube
```
  或WebSearch：
```
"<问题> review"
```
  — 查找视频评测
- 搜索词：
```
"site:news.ycombinator.com <问题>"
```
  — 获取Hacker News上的观点
- WebSearch：
```
"<问题> frustrating OR annoying"
```
  — 更广泛的痛点搜索
- 总结：提炼Top 5痛点，并附上引用原文与来源URL
SEO / ASO分析（取决于步骤2中识别的产品类型）：

网页应用：
- 搜索词：
```
"<竞品> SEO keywords ranking"
```
  — 获取竞品的关键词排名
- 搜索词：
```
"<问题领域> search volume trends 2026"
```
  — 获取需求信号
- 使用WebFetch或MCP
```
include_raw_content
```
  ：爬取竞品页面获取元标签
- 输出结果：关键词表格（关键词、搜索意图、竞争程度、相关性）
移动应用：
- 搜索词：
```
"<分类> App Store top apps keywords 2026"
```
  — 了解分类格局
- 搜索词：
```
"site:reddit.com <竞品应用> review"
```
  — 获取用户投诉
- 输出结果：ASO关键词、竞品评分、常见投诉
命名、域名与企业注册：
- 生成7-10个名称候选（混合描述性名称与原创/品牌化名称）
- 域名可用性：三重验证（whois → dig → RDAP）
- 商标与企业名称冲突检查
查看随本技能附带的
```
references/domain-check.md
```
文件，了解TLD优先级、bash脚本、注意事项以及商标检查方法。
市场规模测算（TAM/SAM/SOM） — 使用WebSearch（主要）：
- WebSearch：
```
"<市场> market size 2025 2026 report"
```
  — 综合多来源数据
- WebSearch：
```
"<市场> growth rate CAGR billion"
```
  — 获取增长预测
- 推导逻辑：TAM → SAM → SOM（第1年）
撰写
research.md
— 将内容写入当前项目目录下的
```
docs/research.md
```
。若目录不存在则创建。
输出总结：
- 核心发现（3-5条要点）
- 建议：推进/放弃/调整方向，并附上简短理由
- 生成的research.md文件路径
- 建议下一步操作：
```
/validate <创意>
```

research.md Format

research.md格式

See

references/research-template.md

(bundled with this skill) for the full output template (frontmatter, 6 sections, tables).

查看随本技能附带的

references/research-template.md

文件，获取完整输出模板（前置元数据、6个章节、表格）。

Notes

注意事项

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

项目目录名称始终使用短横线分隔命名（kebab-case）
若research.md已存在，在覆盖前需询问用户
独立的搜索查询可并行执行

Common Issues

常见问题

MCP web_search not available

MCP web_search不可用

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.

原因： MCP服务器未运行或未配置 解决方法： 以WebSearch/WebFetch作为主要工具。若需更好的引擎路由效果（Reddit、GitHub、YouTube），可搭建SearXNG（私有、自托管、免费）并配置solograph MCP。

Domain check returns wrong results

域名检查结果错误

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.

原因： 未注册的

.app

.dev

域名的whois信息显示的是TLD创建日期 解决方法： 使用三重验证法（whois -> dig -> RDAP）。检查名称服务器与注册商字段，而非创建日期。

research.md already exists

research.md已存在

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

原因： 此前已针对该创意执行过调研 解决方法： 技能会在覆盖前询问用户。可选择合并新发现或重新开始调研。

Proactive Search Practices

主动搜索实践

Reddit Deep Dive

Reddit深度挖掘

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

MCP web_search或WebSearch — 用于发现内容（Reddit查询最多3个关键词），获取帖子URL
MCP Playwright — 打开
```
old.reddit.com
```
URL获取完整帖子+评论（绕过验证码）
提取引用 — 复制关键语句并附上来源（用户名、子版块、日期）
跨帖子检测 — 同一帖子出现在多个子版块意味着更高的参考价值

Product Hunt Research

Product Hunt调研

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

producthunt.com/visit-streaks — 访问 streak排行榜（可通过Playwright爬取）
producthunt.com/@username — 查看用户资料，包含社交链接、创作者历史、积分
PH API v2已损坏 — 自2023年2月起隐藏用户名/Twitter信息，建议使用爬取方式
Apify actors — 在依赖前检查是否已被弃用（2025年9月大规模弃用）

TrustMRR Revenue Validation

TrustMRR收入验证

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

trustmrr.com/startup/<slug>
— 获取Stripe验证的MRR、增长率、订阅数、流量
WebFetch可正常使用 — 无需认证，返回包含JSON-LD结构化数据的完整页面
数据字段： MRR、累计收入、过去30天数据、活跃订阅数、技术栈、流量（24h/7d/30d）、分类、创始人X平台账号
适用场景： 竞品收入验证、基于真实数据的市场规模测算、技术栈发现
搜索方式：
```
"site:trustmrr.com <分类或创意>"
```
查找同类已验证收入的初创公司
Apify爬取工具： TrustMRR Scraper 用于批量提取数据

GitHub Library Discovery

GitHub库发现

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

MCP
engines: github
— 常返回空结果，建议以WebSearch作为主要工具
github.com/topics/<keyword> — 通过Playwright或WebFetch浏览主题页面
检查星标数、最后更新时间、开放问题数 — 避免使用已废弃的仓库

Blocked Content Fallback Chain

内容被屏蔽时的回退流程

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

If a page returns 403/CAPTCHA via WebFetch:

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

MCP Playwright（最佳） → PullPush API（Reddit） → WebFetch → WebSearch片段 → MCP web_search include_raw_content

若WebFetch访问页面返回403/验证码：

Reddit： 使用MCP Playwright →
```
old.reddit.com
```
（始终可用，无验证码）
Reddit搜索： 使用PullPush API
```
api.pullpush.io
```
（结构化JSON，完整帖子正文）
Product Hunt / 其他网站： 使用MCP Playwright
```
browser_navigate
```
（多数网站无验证码）
通用场景： WebSearch片段 + WebSearch内容总结