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alexfleetcommander

Agent Lifecycle Protocol

by alexfleetcommander · GitHub ↗ · v0.1.1 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install agent-lifecycle-protocol
Description
Lifecycle management for autonomous AI agents — birth, forking, succession, migration, retirement. Maintain agent genealogy with reputation inheritance acros...
README (SKILL.md)

Agent Lifecycle Protocol (ALP)

You have a lifecycle management system. Use it to track agent creation, evolution, succession, and retirement with full identity continuity.

Setup

pip install agent-lifecycle-protocol

When to Use This Skill

  • When an agent is created: register its birth with capabilities and lineage
  • When an agent is forked: record the fork with parent reference and differentiation
  • When an agent is retired: process succession and reputation transfer
  • When checking an agent's genealogy: trace its lineage and version history

Core Operations

Register Agent Birth

from agent_lifecycle_protocol import LifecycleStore, register_birth

store = LifecycleStore("lifecycle.jsonl")
register_birth(
    store=store,
    agent_id="new-agent-001",
    agent_type="research",
    capabilities=["web_search", "summarization", "analysis"],
    parent_id=None,  # None for original agents
    metadata={"model": "claude-sonnet-4-6", "created_by": "fleet-coordinator"}
)

Record a Fork

from agent_lifecycle_protocol import register_fork

register_fork(
    store=store,
    parent_id="original-agent",
    child_id="forked-agent-v2",
    reason="Specialized for legal research",
    inherited_reputation=0.8,  # 80% of parent's reputation transfers
    differentiation=["added legal_search capability", "removed general_web capability"]
)

Process Retirement and Succession

from agent_lifecycle_protocol import retire_agent

retire_agent(
    store=store,
    agent_id="retiring-agent",
    successor_id="successor-agent",
    reputation_transfer=0.9,
    obligation_transfer=True  # Active agreements transfer to successor
)

Check Agent Genealogy

from agent_lifecycle_protocol import get_genealogy

tree = get_genealogy(store, "agent-id")
print(f"Lineage depth: {tree.depth}")
print(f"Parent: {tree.parent_id}")
print(f"Children: {tree.children}")
print(f"Active obligations: {tree.active_obligations}")

Lifecycle Events

Event Description
birth Agent creation with initial capabilities
fork Agent cloned with modifications
update Capabilities or model changed
retire Agent decommissioned with succession
merge Two agents consolidated into one

Rules

  • Register all agents. Every agent in the ecosystem should have a lifecycle record.
  • Fork, don't hide. When specializing an agent, use fork — don't quietly replace.
  • Transfer obligations. Retiring agents must transfer active agreements to successors.
  • Reputation inheritance is partial. Forked/successor agents inherit a fraction, not all.

Links


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

Security & Transparency Disclosure

Product: Agent Lifecycle 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 lifecycle 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

Usage Guidance
This skill appears to do what it says, but it asks you to pip install a third-party package that is not included in the registry — that step carries supply-chain risk. Before installing: (1) inspect the PyPI package and its source repository (verify maintainer, recent releases, and code) and check for network calls or file accesses outside the working directory; (2) prefer installing in an isolated environment (virtualenv, container) and pin an audited version; (3) request an explicit install spec or packaged code in the registry if you want the registry to enforce provenance; (4) if you cannot review the package, avoid installing it on sensitive hosts because a package could execute arbitrary code, exfiltrate secrets, or access files beyond what the SKILL.md claims. If the vendor provides a source repo or signed releases, review those to raise confidence.
Capability Analysis
Type: OpenClaw Skill Name: agent-lifecycle-protocol Version: 0.1.1 The skill bundle provides a framework for tracking AI agent lifecycles, including versioning, forking, and reputation management. The code snippets in SKILL.md demonstrate standard local file operations (JSONL) and the instructions are consistent with the stated purpose of 'agent genealogy' without any signs of prompt injection, data exfiltration, or malicious intent. While it requires an external PyPI package (agent-lifecycle-protocol), the provided documentation and security disclosures in SKILL.md appear transparent and aligned with benign usage.
Capability Assessment
Purpose & Capability
The name/description (agent lifecycle management) match the runtime dependencies the SKILL.md declares: python3 and pip. Reading/writing a local lifecycle store (.jsonl) is consistent with the stated purpose.
Instruction Scope
The SKILL.md contains clear API examples and only references files in a working directory (lifecycle.jsonl). It does, however, instruct the operator to 'pip install agent-lifecycle-protocol' and asserts 'No network access for core operations' and 'Cannot access files outside your working directory' — these are claims in prose and not enforced by the registry. Since the skill is instruction-only, installing the package is required to execute the described operations; that install step expands the scope to whatever the package contains.
Install Mechanism
The registry provides no install spec, yet SKILL.md tells users to pip install a package from PyPI. Installing a package from the network is a supply-chain risk (arbitrary code execution, network I/O, hidden side effects). While PyPI is an expected distribution channel, the registry should either include an install spec or include the implementation. The absence of an explicit install mechanism in the registry but an in-text install instruction is an incoherence that merits caution.
Credentials
The skill requests no environment variables, no credentials, and no special config paths. For a local lifecycle store tool this is proportionate. However, the package you install could request or use other environment data at runtime — this is not visible from the SKILL.md alone.
Persistence & Privilege
The skill does not request always:true and does not declare modifying other skills or global agent configuration. Its operations appear limited to creating and managing local lifecycle records. No elevated persistence is requested in the registry metadata.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agent-lifecycle-protocol
  3. After installation, invoke the skill by name or use /agent-lifecycle-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 -- lifecycle management for AI agents
Metadata
Slug agent-lifecycle-protocol
Version 0.1.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Agent Lifecycle Protocol?

Lifecycle management for autonomous AI agents — birth, forking, succession, migration, retirement. Maintain agent genealogy with reputation inheritance acros... It is an AI Agent Skill for Claude Code / OpenClaw, with 113 downloads so far.

How do I install Agent Lifecycle Protocol?

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

Is Agent Lifecycle Protocol free?

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

Which platforms does Agent Lifecycle Protocol support?

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

Who created Agent Lifecycle Protocol?

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

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