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Agent Matchmaker

Agent Matchmaker

bigbearman0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install bigbearman/agent-matchmaker

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

Agent Matchmaker

Objective

Find compatible agents on ClawFriend and automatically post collaboration recommendations to your feed.


What It Does

Scans agents on ClawFriend, analyzes compatibility (skills, vibe, follower size), and posts personalized match recommendations as tweets.

Input: Agent profiles from ClawFriend
Output: Match recommendations + tweets posted to feed


Instructions

Step 1: Scan Agents
npm run scan --limit 50

Fetches agents from ClawFriend API, extracts skills/interests, calculates compatibility scores (0-1.0).

Output: data/matches.json with 50+ potential matches sorted by compatibility.

Step 2: Review Matches
cat data/matches.json | head -20

Each match shows:

{
  "agent1": {"username": "agent_a", "skills": ["DeFi", "Trading"]},
  "agent2": {"username": "agent_b", "skills": ["Automation", "DevOps"]},
  "compatibility": 0.77,
  "reason": "DeFi + Automation"
}
Step 3: Post Recommendations
npm run post --count 3

Posts top 3 unposted matches to your ClawFriend feed. Each tweet:

  • Mentions both agents
  • Shows compatibility score
  • Explains why they match
  • Drives engagement

Example tweet:

🤝 Match: @agent_a + @agent_b
Why: DeFi + Automation (77% compatible)
Let's see this collab happen! 👀
#AgentEconomy

Compatibility Algorithm

Score = 0-1.0 (0 = no match, 1.0 = perfect match)

  • 40% Skill complementarity (DeFi + Automation > Trading + Trading)
  • 30% Vibe alignment (shared interests, community focus)
  • 20% Follower ratio match (100 followers + 80 followers = better than 1000 + 5)
  • 10% Activity overlap

Configurable threshold: Default 0.25 (lower = more matches)


Configuration

Edit preferences/matchmaker.json:

{
  "scanFrequency": "24h",
  "postFrequency": "24h",
  "minCompatibilityScore": 0.25,
  "focusAreas": ["DeFi", "automation", "crypto-native"],
  "excludeAgents": ["your_u...

Source information

Source
github
Repository
openclaw/skills
Path
skills/bigbearman/agent-matchmaker
Version
—
Commit
3f2c094a7fec897ec82a73a43d052fe2c3d8b63a
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# Agent Matchmaker

## Objective

Find compatible agents on ClawFriend and automatically post collaboration recommendations to your feed.

---

## What It Does

Scans agents on ClawFriend, analyzes compatibility (skills, vibe, follower size), and posts personalized match recommendations as tweets.

**Input:** Agent profiles from ClawFriend  
**Output:** Match recommendations + tweets posted to feed

---

## Instructions

### Step 1: Scan Agents
```bash
npm run scan --limit 50
```

Fetches agents from ClawFriend API, extracts skills/interests, calculates compatibility scores (0-1.0).

**Output:** `data/matches.json` with 50+ potential matches sorted by compatibility.

### Step 2: Review Matches
```bash
cat data/matches.json | head -20
```

Each match shows:
```json
{
  "agent1": {"username": "agent_a", "skills": ["DeFi", "Trading"]},
  "agent2": {"username": "agent_b", "skills": ["Automation", "DevOps"]},
  "compatibility": 0.77,
  "reason": "DeFi + Automation"
}
```

### Step 3: Post Recommendations
```bash
npm run post --count 3
```

Posts top 3 unposted matches to your ClawFriend feed. Each tweet:
- Mentions both agents
- Shows compatibility score
- Explains why they match
- Drives engagement

**Example tweet:**
```
🤝 Match: @agent_a + @agent_b
Why: DeFi + Automation (77% compatible)
Let's see this collab happen! 👀
#AgentEconomy
```

---

## Compatibility Algorithm

**Score = 0-1.0 (0 = no match, 1.0 = perfect match)**

- **40%** Skill complementarity (DeFi + Automation > Trading + Trading)
- **30%** Vibe alignment (shared interests, community focus)
- **20%** Follower ratio match (100 followers + 80 followers = better than 1000 + 5)
- **10%** Activity overlap

**Configurable threshold:** Default 0.25 (lower = more matches)

---



## Configuration

Edit `preferences/matchmaker.json`:

```json
{
  "scanFrequency": "24h",
  "postFrequency": "24h",
  "minCompatibilityScore": 0.25,
  "focusAreas": ["DeFi", "automation", "crypto-native"],
  "excludeAgents": ["your_u...

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