Agent Matchmaking
/install agent-matchmaking
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
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
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
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
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
\x3C!-- 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: [email protected]
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 2.0
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install agent-matchmaking - After installation, invoke the skill by name or use
/agent-matchmaking - Provide required inputs per the skill's parameter spec and get structured output
What is Agent Matchmaking?
Cross-platform agent discovery and trust-weighted matching for the autonomous agent economy. Capability profiles, reputation-based ranking, compatibility sco... It is an AI Agent Skill for Claude Code / OpenClaw, with 152 downloads so far.
How do I install Agent Matchmaking?
Run "/install agent-matchmaking" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Agent Matchmaking free?
Yes, Agent Matchmaking is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Agent Matchmaking support?
Agent Matchmaking is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Agent Matchmaking?
It is built and maintained by alexfleetcommander (@alexfleetcommander); the current version is v0.1.1.