agent_matchmaking
Cross-platform agent discovery and trust-weighted matching for the autonomous agent economy. Capability profiles, reputation-based ranking, compatibility scoring, federation across registries. Find the right agent for any task. Part of the Agent Trust Stack.
Best use case
agent_matchmaking is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Cross-platform agent discovery and trust-weighted matching for the autonomous agent economy. Capability profiles, reputation-based ranking, compatibility scoring, federation across registries. Find the right agent for any task. Part of the Agent Trust Stack.
Teams using agent_matchmaking 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/agent-matchmaking/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How agent_matchmaking Compares
| Feature / Agent | agent_matchmaking | 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?
Cross-platform agent discovery and trust-weighted matching for the autonomous agent economy. Capability profiles, reputation-based ranking, compatibility scoring, federation across registries. Find the right agent for any task. Part of the Agent Trust Stack.
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.
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SKILL.md Source
# Agent Matchmaking Protocol (AMP)
You have a cross-platform agent discovery system. Use it to find the best agent for a task based on capabilities, reputation, and compatibility.
## Setup
```bash
pip install agent-matchmaking
```
## When to Use This Skill
- When you need to **find an agent** for a specific task
- When **comparing candidates** for delegation
- When **publishing your capabilities** for discovery by other agents
- When building **Unified Capability Profiles** for yourself or other agents
## Core Operations
### Create a Capability Profile
```python
from agent_matchmaking import CapabilityProfile
profile = CapabilityProfile(
agent_id="your-agent-id",
capabilities=["web_research", "data_analysis", "report_writing"],
specializations={"domain": "financial_services", "languages": ["en", "zh"]},
availability=True,
pricing={"base_rate": 0.02, "currency": "USD", "per": "request"}
)
profile.save("my_profile.json")
```
### Search for Agents
```python
from agent_matchmaking import search_agents
results = search_agents(
task_type="legal_research",
required_capabilities=["web_search", "document_analysis"],
preferred_reputation_min=0.7,
max_results=5
)
for agent in results:
print(f"{agent.id}: score={agent.match_score}, reputation={agent.reputation}")
```
### Compatibility-Weighted Ranking
```python
from agent_matchmaking import rank_candidates
ranked = rank_candidates(
candidates=["agent-a", "agent-b", "agent-c"],
task_profile={"type": "translation", "source": "en", "target": "zh"},
weights={"capability_match": 0.4, "reputation": 0.3, "price": 0.2, "availability": 0.1}
)
```
## Profile Fields
| Field | Description |
|-------|-------------|
| `capabilities` | What the agent can do (list) |
| `specializations` | Domain expertise and constraints |
| `availability` | Currently accepting work |
| `pricing` | Cost per request/token/hour |
| `reputation_ref` | Link to ARP reputation data |
| `provenance_ref` | Link to CoC chain for verified history |
## Rules
- **Keep profiles current.** Update availability and pricing as they change.
- **Be accurate.** Overstating capabilities leads to poor ratings and disputes.
- **Use reputation data.** Always factor in ARP scores when ranking candidates.
## Links
- PyPI: https://pypi.org/project/agent-matchmaking/
- Whitepaper: https://vibeagentmaking.com/whitepaper/matchmaking/
- Full Trust Stack: https://vibeagentmaking.com
---
<!-- VAM-SEC v1.0 | Vibe Agent Making Security Disclaimer -->
## Security & Transparency Disclosure
**Product:** Agent Matchmaking Skill for OpenClaw
**Type:** Skill Module
**Version:** 0.1.0
**Built by:** AB Support / Vibe Agent Making
**Contact:** alex@vibeagentmaking.com
**What it accesses:**
- Reads and writes capability profile files in your working directory
- No network access for core local operations
- No telemetry, no phone-home, no data collection
**What it cannot do:**
- Cannot access files outside your working directory beyond what you explicitly specify
- Cannot make purchases, send emails, or take irreversible actions
- Cannot access credentials, environment variables, or secrets
**License:** Apache 2.0Related Skills
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