network-matcher

Matches portfolio company needs with investor network resources

509 stars

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

$curl -o ~/.claude/skills/network-matcher/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/business/venture-capital/skills/network-matcher/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/network-matcher/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How network-matcher Compares

Feature / Agentnetwork-matcherStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/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

Related Skills

Network Protocol Analysis Skill

509
from a5c-ai/babysitter

Network protocol capture, analysis, and fuzzing capabilities

network-performance

509
from a5c-ai/babysitter

Expert skill for network performance analysis and optimization. Analyze packet captures, identify network latency bottlenecks, configure TCP tuning parameters, analyze connection pooling behavior, debug TLS handshake performance, and optimize HTTP/2 and HTTP/3 settings.

network-testing

509
from a5c-ai/babysitter

Comprehensive network testing, benchmarking, and performance validation skill

network-simulation

509
from a5c-ai/babysitter

Skill for network condition simulation, emulation, and chaos engineering

unreal-networking

509
from a5c-ai/babysitter

Unreal Engine networking skill for replication, RPCs, relevancy, and dedicated server architecture.

steamworks-networking

509
from a5c-ai/babysitter

Steam P2P networking skill for lobbies and relay servers.

p2p-networking

509
from a5c-ai/babysitter

Peer-to-peer networking skill for NAT punch-through and relay servers.

godot-networking

509
from a5c-ai/babysitter

Godot multiplayer skill for high-level networking API, RPCs, and peer-to-peer networking.

network-analysis

509
from a5c-ai/babysitter

Map and analyze social network structures using centrality measures, community detection, and visualization tools like Gephi or UCINET

network-visualizer

509
from a5c-ai/babysitter

Skill for visualizing network and graph data

tensor-network-simulator

509
from a5c-ai/babysitter

Tensor network-based simulation skill for large circuit approximation

quimb-tensor-network

509
from a5c-ai/babysitter

QuTiP/quimb tensor network skill for quantum many-body simulations and entanglement analysis