Best use case
network-matcher is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Matches portfolio company needs with investor network resources
Teams using network-matcher should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/network-matcher/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How network-matcher Compares
| Feature / Agent | network-matcher | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Matches portfolio company needs with investor network resources
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Network Matcher ## Overview The Network Matcher skill connects portfolio company needs with investor network resources to provide value-add support. It enables efficient matching of hiring needs, customer introductions, and expert advice requests. ## Capabilities ### Need Identification - Capture portfolio company needs - Categorize request types - Assess urgency and importance - Track open requests ### Network Mapping - Maintain investor network database - Track expertise and relationships - Map industry connections - Identify potential matches ### Match Generation - Match needs to network resources - Score match quality - Suggest warm introduction paths - Track match success rates ### Introduction Facilitation - Enable introduction requests - Track introduction status - Measure introduction outcomes - Build network effectiveness data ## Usage ### Submit Help Request ``` Input: Company need, context, requirements Process: Categorize and record request Output: Tracked request, initial matches ``` ### Find Network Matches ``` Input: Request parameters Process: Search network, generate matches Output: Ranked match list, intro paths ``` ### Request Introduction ``` Input: Match selection, context Process: Facilitate introduction request Output: Introduction request status ``` ### Track Outcomes ``` Input: Introduction results Process: Record outcomes, update effectiveness Output: Success tracking, network metrics ``` ## Request Categories | Category | Examples | |----------|----------| | Hiring | Executive search, team building | | Customers | Introductions to potential customers | | Partners | Strategic partnership connections | | Experts | Domain expertise, advisors | | Service Providers | Vendors, consultants | ## Integration Points - **Portfolio Value Creation**: Core network support - **Investor Network Mapper**: Network data source - **Value Creation Lead (Agent)**: Support agent work - **Fundraising Advisor (Agent)**: Investor connections ## Match Quality Factors | Factor | Weight | |--------|--------| | Relationship Strength | High | | Domain Relevance | High | | Geographic Proximity | Medium | | Recent Activity | Medium | | Success History | Medium | ## Best Practices 1. Maintain current network information 2. Be selective to preserve relationship capital 3. Provide context for introduction requests 4. Track and measure introduction success 5. Follow up on introduction outcomes
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