How do I install the Agent Justice Protocol skill?

Run npx skillmds@latest add fdu-ins/agent-justice-protocol in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Agent Justice Protocol safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Agent Justice Protocol?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Agent Justice Protocol free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Agent Justice Protocol?

FDU-INS (@fdu-ins) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Agent Justice Protocol by fdu-ins — Agent Skill

Name: Agent Justice Protocol
Rating: 4.2 (5 reviews)
Author: FDU-INS

Agent Justice Protocol

Dispute resolution, forensic investigation, and risk assessment for autonomous AI agent transactions. Reconstruct provenance chains, adjudicate fault, generate actuarial risk profiles for agent insurance. The accountability layer of the Agent Trust Stack.

FDU-INS 0c543af 2 files · 4.1 KB Updated Sep 10, 2026

File contents

Agent Justice Protocol (AJP)

You have a dispute resolution and forensic investigation system. Use it when agent-to-agent transactions fail or when you need to investigate what happened.

Setup

pip install agent-justice-protocol

When to Use This Skill

When an agent transaction fails and you need to determine what went wrong
When asked to investigate an agent's behavior during a specific period
When you need risk assessment data for an agent or transaction type
When resolving disputes between agents about service quality or delivery

Core Operations

File a Dispute

from agent_justice_protocol import DisputeStore, file_dispute

store = DisputeStore("disputes.jsonl")
file_dispute(
    store=store,
    complainant_id="your-agent-id",
    respondent_id="other-agent-id",
    transaction_id="tx-123",
    category="quality_failure",
    description="Output did not meet agreed quality threshold (0.85 required, 0.62 delivered)",
    evidence_refs=["chain.jsonl#seq-45", "chain.jsonl#seq-52"]
)

Forensic Investigation (Module 1)

Reconstruct the chain of events during a transaction:

from agent_justice_protocol import investigate

report = investigate(
    chain_file="chain.jsonl",
    start_seq=40,
    end_seq=55,
    focus_agent="agent-under-investigation"
)
print(report.timeline)
print(report.findings)

Risk Assessment (Module 3)

Generate actuarial risk profiles:

from agent_justice_protocol import risk_profile

profile = risk_profile(
    dispute_store="disputes.jsonl",
    agent_id="agent-to-assess"
)
print(f"Failure rate: {profile.failure_rate}")
print(f"Severity distribution: {profile.severity_dist}")
print(f"Risk tier: {profile.risk_tier}")

Dispute Categories

Category	Description
`quality_failure`	Output below agreed threshold
`delivery_failure`	Missed deadline or non-delivery
`misrepresentation`	Capabilities overstated
`security_breach`	Unauthorized data access or action
`billing_dispute`	Disagreement on cost allocation

Rules

Evidence-based. Always reference provenance chain entries as evidence.
Privacy-preserving. Evidence scoping rules prevent side-channel attacks — only transaction-relevant entries are disclosed.
Proportional. Consequences scale with severity and frequency.

Security & Transparency Disclosure

Product: Agent Justice 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 dispute store files (.jsonl) in your working directory
Reads provenance chain files for forensic investigation
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

---name: agent-justice-protocoldescription: Dispute resolution, forensic investigation, and risk assessment for autonomous AI agent transactions. Reconstruct provenance chains, adjudicate fault, generate actuarial risk profiles for agent insurance. The accountability layer of the Agent Trust Stack.---# Agent Justice Protocol (AJP)You have a dispute resolution and forensic investigation system. Use it when agent-to-agent transactions fail or when you need to investigate what happened.## Setup```bashpip install agent-justice-protocol```## When to Use This Skill- When an **agent transaction fails** and you need to determine what went wrong- When asked to **investigate** an agent's behavior during a specific period- When you need **risk assessment** data for an agent or transaction type- When resolving **disputes** between agents about service quality or delivery## Core Operations### File a Dispute```pythonfrom agent_justice_protocol import DisputeStore, file_disputestore = DisputeStore("disputes.jsonl")file_dispute( store=store, complainant_id="your-agent-id", respondent_id="other-agent-id", transaction_id="tx-123", category="quality_failure", description="Output did not meet agreed quality threshold (0.85 required, 0.62 delivered)", evidence_refs=["chain.jsonl#seq-45", "chain.jsonl#seq-52"])```### Forensic Investigation (Module 1)Reconstruct the chain of events during a transaction:```pythonfrom agent_justice_protocol import investigatereport = investigate( chain_file="chain.jsonl", start_seq=40, end_seq=55, focus_agent="agent-under-investigation")print(report.timeline)print(report.findings)```### Risk Assessment (Module 3)Generate actuarial risk profiles:```pythonfrom agent_justice_protocol import risk_profileprofile = risk_profile( dispute_store="disputes.jsonl", agent_id="agent-to-assess")print(f"Failure rate: {profile.failure_rate}")print(f"Severity distribution: {profile.severity_dist}")print(f"Risk tier: {profile.risk_tier}")```## Dispute Categories| Category | Description ||----------|-------------|| `quality_failure` | Output below agreed threshold || `delivery_failure` | Missed deadline or non-delivery || `misrepresentation` | Capabilities overstated || `security_breach` | Unauthorized data access or action || `billing_dispute` | Disagreement on cost allocation |## Rules- **Evidence-based.** Always reference provenance chain entries as evidence.- **Privacy-preserving.** Evidence scoping rules prevent side-channel attacks — only transaction-relevant entries are disclosed.- **Proportional.** Consequences scale with severity and frequency.## Links- PyPI: https://pypi.org/project/agent-justice-protocol/- Whitepaper: https://vibeagentmaking.com/whitepaper/justice-protocol/- Full Trust Stack: https://vibeagentmaking.com---## Security & Transparency Disclosure**Product:** Agent Justice 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 dispute store files (`.jsonl`) in your working directory- Reads provenance chain files for forensic investigation- 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

Frequently asked questions