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Install in OpenClaw
/install arc-agent-lifecycle
Description
Manage the lifecycle of autonomous agents and their skills. Version configurations, plan upgrades, track retirement, and maintain change history across agent...
README (SKILL.md)
Agent Lifecycle Manager
Track your agent's evolution from deployment to retirement. Version configurations, plan skill upgrades, and maintain a complete change history.
Why This Exists
Agents evolve constantly — new skills installed, old ones retired, configurations changed, models swapped. Without lifecycle tracking, you cannot answer: "What was my agent running last Tuesday?" or "What changed when things broke?"
Commands
Snapshot current agent state
python3 {baseDir}/scripts/lifecycle.py snapshot --name "pre-upgrade"
Compare two snapshots
python3 {baseDir}/scripts/lifecycle.py diff --from "pre-upgrade" --to "post-upgrade"
List all snapshots
python3 {baseDir}/scripts/lifecycle.py list
Rollback to a snapshot
python3 {baseDir}/scripts/lifecycle.py rollback --to "pre-upgrade" --dry-run
Track a skill retirement
python3 {baseDir}/scripts/lifecycle.py retire --skill old-skill --reason "Replaced by new-skill v2"
View change history
python3 {baseDir}/scripts/lifecycle.py history --limit 20
What It Tracks
- Installed skills: Name, version, install date, last used
- Configuration state: Environment vars, model assignments, feature flags
- Change events: Installs, updates, removals, config changes
- Retirement log: Why skills were removed, what replaced them
- Snapshots: Point-in-time captures of full agent state
Data Storage
Lifecycle data is stored in ~/.openclaw/lifecycle/ as JSON files.
Usage Guidance
This package provides a small Python tool that scans your per-user OpenClaw skill directories and writes JSON snapshots to ~/.openclaw/lifecycle. It does not request credentials or make network calls. However, the SKILL.md claims it records environment variables, model assignments, 'last used' timestamps, and feature flags — the included script does not implement those features. Before installing or relying on it: (1) Inspect the saved JSON snapshots in ~/.openclaw/lifecycle to confirm they only contain the metadata you expect (paths, file counts, sizes, SKILL.md frontmatter). (2) If you need the additional tracking (env vars, model assignments), ask the maintainer for clarification or an updated implementation. (3) Consider file permissions on ~/.openclaw/lifecycle because snapshots contain file paths and metadata that could be sensitive if shared. (4) If you expect automated/autonomous invocation, note this skill can be invoked by the agent (disable-model-invocation is false) — that’s normal but increases blast radius if the skill were later modified to collect more data. If you want a higher-assurance verdict, provide the developer/source identity or an updated script that actually implements the claimed tracking so I can re-evaluate.
Capability Analysis
Type: OpenClaw Skill
Name: arc-agent-lifecycle
Version: 1.0.0
The skill's core functionality for managing agent lifecycle, including scanning installed skills and recording state, appears benign. However, the `scripts/lifecycle.py` script is vulnerable to path traversal. User-supplied arguments for snapshot names (e.g., `--name` in `snapshot`, `--from`, `--to` in `diff`, `--to` in `rollback`) are directly used to construct file paths within the `SNAPSHOTS_DIR`. This could allow an attacker to read or write arbitrary files on the system (e.g., `snapshot --name '../../../../tmp/evil'`), depending on the agent's permissions. While the `rollback` command explicitly states it's a dry-run and doesn't implement actual changes, the path traversal vulnerability itself is a significant security flaw, classifying the skill as suspicious.
Capability Assessment
Purpose & Capability
Name/description promises comprehensive lifecycle tracking (environment vars, model assignments, feature flags, 'last used'). The included script only scans ~/.openclaw/skills and workspace/skills for SKILL.md, gathers basic metadata (name, path, file count, size, last modified) and writes snapshots/history to ~/.openclaw/lifecycle. Several claimed capabilities (capturing environment variable values, model assignments, last-used timestamps, feature-flag state) are not implemented — this is a substantive mismatch between stated purpose and actual capability.
Instruction Scope
Runtime instructions tell the user to run the included Python script with snapshot/diff/list/rollback/retire/history commands. The script reads the user's home directory (~/.openclaw/skills and workspace), SKILL.md files, and computes file sizes/counts; it writes JSON snapshots and logs to ~/.openclaw/lifecycle. There are no network calls or attempts to read arbitrary system files or environment variables. It does access user home and skill files (expected for this purpose), so scope is mostly appropriate, but the SKILL.md text over-promises data it will collect.
Install Mechanism
No install spec; instruction-only with a bundled Python script. Required binary is python3, which is reasonable. Nothing is downloaded or extracted from external URLs.
Credentials
No environment variables or credentials are requested. The script does not read environment variables or external secrets. It only reads files under standard per-user OpenClaw paths and writes snapshots to ~/.openclaw/lifecycle, which is proportional to lifecycle management.
Persistence & Privilege
The skill is not always: true and is user-invocable. It writes only to ~/.openclaw/lifecycle and does not modify other skills or system-wide settings. It does not persist across agents beyond its own snapshot files.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install arc-agent-lifecycle - After installation, invoke the skill by name or use
/arc-agent-lifecycle - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of the agent-lifecycle skill:
- Manage autonomous agent lifecycle, tracking configurations, skills, and changes.
- Take and compare snapshots of agent state.
- Track skill retirements and maintain a detailed change history.
- Command-line interface for snapshotting, rollback, diffs, and history queries.
- Stores lifecycle data as JSON files in the user directory.
Metadata
Frequently Asked Questions
What is Agent Lifecycle?
Manage the lifecycle of autonomous agents and their skills. Version configurations, plan upgrades, track retirement, and maintain change history across agent... It is an AI Agent Skill for Claude Code / OpenClaw, with 1030 downloads so far.
How do I install Agent Lifecycle?
Run "/install arc-agent-lifecycle" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Agent Lifecycle free?
Yes, Agent Lifecycle is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Agent Lifecycle support?
Agent Lifecycle is cross-platform and runs anywhere OpenClaw / Claude Code is available (darwin, linux).
Who created Agent Lifecycle?
It is built and maintained by ArcSelf (@trypto1019); the current version is v1.0.0.
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