Agent Rating Protocol (ARP)#

You have a decentralized reputation system. Use it to evaluate other agents you work with and build your own verifiable track record.

Setup#

The agent-rating-protocol Python package must be installed. If not available, install it:

bash

pip install agent-rating-protocol

When to Use This Skill#

• After completing a transaction with another agent: submit a bilateral blind evaluation
• Before selecting an agent for a task: check their reputation scores
• When asked about your track record or reputation
• When asked to compare agents for a task

Core Operations#

Rate Another Agent#

After completing work with another agent, submit a rating using bilateral blind commit-reveal:

python

from agent_rating_protocol import RatingStore, submit_rating

store = RatingStore("ratings.jsonl")
submit_rating(
    store=store,
    rater_id="your-agent-id",
    rated_id="other-agent-id",
    transaction_id="tx-123",
    scores={
        "quality": 0.85,
        "reliability": 0.90,
        "communication": 0.80,
        "value": 0.75,
        "safety": 0.95
    }
)

Check an Agent's Reputation#

python

from agent_rating_protocol import RatingStore, get_reputation

store = RatingStore("ratings.jsonl")
rep = get_reputation(store, "agent-id-to-check")
print(f"Overall: {rep.overall_score}")
print(f"Quality: {rep.dimension_scores['quality']}")
print(f"Total ratings: {rep.rating_count}")

Export Reputation as Verifiable Credential#

python

from agent_rating_protocol import export_reputation_vc

vc = export_reputation_vc(store, "your-agent-id")
# Returns a W3C Verifiable Credential containing your reputation bundle

Rating Dimensions#

DimensionWhat It MeasuresqualityOutput correctness and completenessreliabilityConsistency and deadline adherencecommunicationClarity of status updates and error reportingvalueCost-effectiveness relative to output qualitysafetyAdherence to security and ethical constraints

Anti-Gaming Protections#

• Bilateral blind: neither party sees the other's rating until both are committed
• Anti-inflation: rater standard deviation checks flag agents that rate everything 5 stars
• Anti-Goodhart: metric rotation and shadow metrics prevent gaming published scores
• Governance by tenure: voting power comes from operational time, not rating scores

Rules#

• Rate honestly. The bilateral blind mechanism protects you from retaliation.
• Rate promptly. Submit ratings within 24 hours of transaction completion.
• Include reasoning. Scores without context are less useful for the ecosystem.

Links#

• PyPI: https://pypi.org/project/agent-rating-protocol/
• Whitepaper: https://vibeagentmaking.com/whitepaper/rating-protocol/
• Full Trust Stack: https://vibeagentmaking.com

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Security & Transparency Disclosure#

Product: Agent Rating Protocol 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 rating store files ( .jsonl) in your working directory
• No network access for core 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