Solo Research

/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
• web_extract(url, size, page) — one page as clean markdown, boilerplate removed
• 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. For reading one page in full, prefer web_extract over include_raw_content: it runs trafilatura, so navigation and footers are gone and tables survive. size="s|m|l" caps at 5k/10k/25k chars, size="f" paginates the whole document and page=2 walks it. 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_extract / web_search raw     ← 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:

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	MCP web_extract (fallback: WebFetch)	Clean markdown, size=f + page=n for long docs
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

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.)

3. 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.

4. 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.

5. 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)

6. 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

7. 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

8. 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.

9. 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.

10. 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.

11. 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)

12. Write research.md — write to docs/research.md in the current project directory. Create the directory if needed.

13. 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/<keyword> — 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