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Category: Research · Version: 0.0.1 · Author: opendirectory · Compatibility: All targets (claude, codex, opencode, gemini, anti-gravity, openclaw, hermes)
Give the skill a product URL or description. It detects the industry and funding stage, identifies 5 comparable funded companies, searches who backed those companies (Track A), finds VCs who publish investment theses about this space (Track B), and returns a ranked sourced investor list with deep-dives and outreach hooks.

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Install

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What It Does

  • Fetches the product URL via Firecrawl (handles JS-rendered SPAs) or Tavily extract as fallback
  • Detects funding stage from CTA signals on the page (waitlist, free trial, pricing, sales CTAs)
  • Maps a 3-level industry taxonomy (L1 > L2 > L3) from the product page
  • Curated pre-match (Step 5b): Scores product against a verified dataset of 25 VC funds (sourced from fund websites) — instant zero-hallucination matches with no Tavily credits consumed
  • Discovers comparable companies: Curated portfolio companies from matched funds + Tavily live search for L3-niche specifics
  • Track A: 5 Tavily searches to find who invested in each comparable company
  • Track B: 3 Tavily searches to find VCs who publish investment theses about this specific niche
  • Synthesizes and ranks all found VCs — curated matches labeled “verified”, Tavily matches labeled by track
  • Produces top 5 deep-dives with fund overview, portfolio evidence, how-to-approach, and outreach hook
  • Generates 3 product-specific outreach hooks (not generic advice)
  • Saves output to docs/vc-intel/[product]-[date].md
Zero-hallucination guarantee: Every VC name, fund detail, check size, portfolio company, and thesis source in the output must trace to either (a) the curated data/vc_funds.json dataset (sourced from fund websites) or (b) a specific Tavily search result. The AI does not draw from training knowledge for any factual claim.

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Requirements

Tavily is required. Firecrawl is recommended — without it, Tavily extract is used as fallback (may miss JS-rendered content).

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Setup

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How to Use

Or paste a product description directly if the URL is behind a login or returns no readable content.

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Why Two Tracks

Track A (portfolio mapping): VCs who already wrote a check in your space. These investors have proven they understand the category, the risks, and the buyer. They need less convincing than a generalist fund. Track B (thesis matching): VCs who are actively publishing about your space. An investor who wrote a 2,000-word blog post about why they want to invest in CI/CD tooling is actively looking for deals. Your cold email lands in a much warmer inbox. Generic “VCs in B2B SaaS” lists skip both signals. This skill produces only VCs with named evidence for each entry.

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Output

Each run produces:
  1. Product analysis: detected industry taxonomy, stage, ICP, comparable companies used
  2. Track A table: VCs who backed comparable companies (with evidence)
  3. Track B table: VCs with published theses about this space (with source)
  4. Top 5 deep-dives: fund overview, why it fits, portfolio in space, how to approach, outreach hook
  5. 3 outreach hooks: product-specific openers for cold outreach

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Cost per Run

  • Firecrawl: ~$0.001 per fetch
  • Tavily: 10 searches at ~0.01each= 0.01 each = ~0.10 (2 comparable discovery + 5 Track A + 3 Track B)
  • Curated pre-match (Step 5b): $0.00 — local scoring against data/vc_funds.json, no API calls
  • Total: ~$0.10 per run

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Project Structure

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License

MIT