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varnan-tech/opendirectory

vc-curated-match

Accepts a product description and URL to algorithmically identify relevant Venture Capital investors targeting exactly that stage, industry, and niche based on a curated static dataset.

First seen May 2, 2026

Installation

$ npx skills add varnan-tech/opendirectory --skill vc-curated-match
View on skills.sh ↗ GitHub repository ↗

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 636
License LICENSE
Default branch main
Open issues 1
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.0.0

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,509 B
  • docs README.md 5,186 B
  • docs SUMMARY.md 209 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 30 installs

SKILL.md

VC Curated Match Skill

Identify targeted VC funds based on a product's description and URL.

When to Trigger This Skill

Use this skill when the user asks to:

  • Find investors for their startup or open-source project.
  • Get a list of relevant VC funds by stage, industry, or space.
  • Match their product built with specific technologies to investor theses.

Step 1: Confirm Input

Ask the user for the product description and the URL. Optional parameters:

  • Stage: Pre-Seed, Seed, Series A (--stage)
  • Output: e.g., vc-matches.md (--output)

Step 2: Fetch Matches & Generate Report

Run the orchestrator script to handle context fetching, VC matching, and Markdown generation in one command.

python scripts/run.py --description "A fast rust-based web framework" --url "https://example.com"

For custom requests, append overrides:

python scripts/run.py \
  --description "..." \
  --url "..." \
  [--stage Seed] \
  [--output matched-investors.md]

Step 3: Present Results

Summarize the closest matches returned. Mention high-confidence matches explicitly. Provide the output path.

Dependencies

Standard Python 3.10+ library (no external packages required).