Agent Lifecycle Protocol

Lifecycle management for autonomous AI agents — birth, forking, succession, migration, retirement. Maintain agent genealogy with reputation inheritance across versions. Identity continuity when agents evolve. Part of the Agent Trust Stack.

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

bash

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

python

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

python

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

python

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

python

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

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

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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: [e-mail]

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