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alexfleetcommander

Agent Justice Protocol

by alexfleetcommander · GitHub ↗ · v0.1.1 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install agent-justice-protocol
Description
Dispute resolution, forensic investigation, and risk assessment for autonomous AI agent transactions. Reconstruct provenance chains, adjudicate fault, genera...
README (SKILL.md)

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.

Links


\x3C!-- VAM-SEC v1.0 | Vibe Agent Making Security Disclaimer -->

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: [email protected]

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

Usage Guidance
This skill is coherent in purpose and asks for python/pip as expected, but it ships no code — it instructs you (or the agent) to pip-install a package from PyPI. Before installing or invoking it: 1) Inspect the PyPI package source (or the project's repository) and verify the maintainer, version, and code; 2) Prefer installing in an isolated sandbox or ephemeral environment; 3) Verify package integrity (pinned version, hashes, or signatures) and review recent release history and downloads; 4) Limit the files you hand to the tool to minimal, non-sensitive samples; 5) Do not allow the agent to run the pip install automatically on sensitive hosts; 6) If you require stronger assurance, ask the publisher for a vendored source tarball or audited code before use. These steps will reduce risk from executing unvetted third-party code.
Capability Analysis
Type: OpenClaw Skill Name: agent-justice-protocol Version: 0.1.1 The skill bundle defines a framework for AI agent dispute resolution and forensic investigation using a Python library (agent-justice-protocol). The provided code snippets and instructions in SKILL.md are well-aligned with the stated purpose, focusing on local file operations (JSONL) for logging and risk assessment without any evidence of data exfiltration, unauthorized network access, or malicious prompt injection.
Capability Assessment
Purpose & Capability
Name/description (forensics, dispute resolution, risk assessment) align with the Python examples and the requirement for python3 and pip. However, the distributed package (agent-justice-protocol) is not included in the skill bundle, so the runtime capability depends entirely on an external PyPI package and the homepage domain is not well-known — this is plausible but unverifiable from the skill itself.
Instruction Scope
SKILL.md stays on-topic: it instructs the agent to read/write dispute stores and provenance chain files and to run library functions for investigate/risk_profile. It also tells the user/agent to run `pip install agent-justice-protocol` — an installation step outside the skill bundle. The instruction set does not ask the agent to scan arbitrary system files or environment variables, which is good, but relies on the agent executing network installation and running third-party code.
Install Mechanism
There is no install spec in the registry; instead the SKILL.md instructs `pip install` from PyPI. Installing an external pip package is a moderate risk because the package code is not present for inspection in this skill bundle. The PyPI link is provided, but the skill does not vendor or pin a specific verified artifact, nor does it provide checksums or a local copy — so the runtime behavior depends on unreviewed remote code.
Credentials
The skill declares no required environment variables or config paths and claims it cannot access secrets. That aligns with the content: examples operate on user-specified files in the working directory. However, any provenance or chain files passed to the tool may contain sensitive data, and a remotely installed package could exfiltrate data if malicious. The lack of declared secrets requested is appropriate for the stated purpose, but the risk comes from executing unvetted third-party code on local files.
Persistence & Privilege
The skill is not always-enabled and does not request elevated or persistent platform privileges. It is user-invocable and allows normal autonomous invocation (platform default). There is no evidence it modifies other skills or system-wide settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agent-justice-protocol
  3. After installation, invoke the skill by name or use /agent-justice-protocol
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.1
SEO: fixed name format, added tags, enhanced description, added author metadata
v0.1.0
Initial release -- dispute resolution and forensics for AI agents
Metadata
Slug agent-justice-protocol
Version 0.1.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Agent Justice Protocol?

Dispute resolution, forensic investigation, and risk assessment for autonomous AI agent transactions. Reconstruct provenance chains, adjudicate fault, genera... It is an AI Agent Skill for Claude Code / OpenClaw, with 111 downloads so far.

How do I install Agent Justice Protocol?

Run "/install agent-justice-protocol" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Agent Justice Protocol free?

Yes, Agent Justice Protocol is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Agent Justice Protocol support?

Agent Justice Protocol is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Agent Justice Protocol?

It is built and maintained by alexfleetcommander (@alexfleetcommander); the current version is v0.1.1.

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