# Agent Lifecycle Manager

> >

- **Type:** Skill
- **Install:** `agentstack add skill-liqiongyu-my-agents-agent-lifecycle-manager`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [liqiongyu](https://agentstack.voostack.com/s/liqiongyu)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [liqiongyu](https://github.com/liqiongyu)
- **Source:** https://github.com/liqiongyu/my-agents/tree/main/skills/agent-lifecycle-manager

## Install

```sh
agentstack add skill-liqiongyu-my-agents-agent-lifecycle-manager
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Agent Lifecycle Manager

Manage agent packages (`agent.json`, `claude-code.md`, `codex.toml`, `CHANGELOG.md`) as a lifecycle, not isolated file edits. This skill routes the request to the right stage, runs it, and closes the loop.

## Route First

Classify the request before doing anything:

| Stage | When | Key action |
| --- | --- | --- |
| **Create / Update** | New agent or material revision | Write the 3 authored files with minimal instructions |
| **Validate** | After any change | `npm test` + `quick_validate_agent.py` |
| **Evaluate** | Test on realistic prompts | `seed_eval_workspace.py` + `run_surface_eval.py` |
| **Optimize** | Under/over-triggering | Tighten description wording |
| **Install** | Activate on a surface | `npm run install-agent` |
| **Audit** | Library health check | `audit_agent_inventory.py` |

Summarize the chosen route in one sentence before proceeding.

## Creation Gate

Before creating a new agent, answer these questions honestly. If most answers are "no", don't create it.

1. **Does a dedicated agent add value beyond inline execution?** Value can come from behavioral differences (the model wouldn't do this by default), context isolation (keeps the main agent's window clean), result compression (returns a summary instead of raw process), parallelism (can run alongside other agents), or permission narrowing (read-only scope). At least one must apply.
2. **Can you name the behavioral contract?** An agent needs to enforce something specific — an output format, a safety boundary, a collaboration protocol, a workflow the model wouldn't follow unprompted. If you can't articulate it, there's no agent here.
3. **Is there an existing agent that could be slightly adjusted instead?** Prefer tightening an existing agent over creating a new one with overlapping scope.
4. **Will this be spawned frequently enough to justify its existence?** One-off workflows don't need agents. Agents are for recurring patterns.
5. **Can you write the instructions concisely?** Official examples use 1-5 sentences. If you need 50+ lines, you're probably teaching the model things it already knows — strip to behavioral contract only, or split the scope.

If the agent passes the gate, proceed to Create / Update.

## Create / Update

Agent instructions should be **narrow and opinionated** — 5-8 lines of behavioral contract, not a teaching manual. The model already knows how to search, review, plan, and debug. Only specify:

- Role boundary (read-only? write? what scope?)
- Output contract (what to return, in what shape)
- Safety rails (what to never do)

Use `npm run new -- --agent ` for a fresh scaffold. Keep semantics aligned across `agent.json`, `claude-code.md`, and `codex.toml` — one routing boundary, one role, same instructions.

For Codex agents, set `sandbox_mode`, `model`, and `model_reasoning_effort` explicitly rather than inheriting from the parent session.

Read [platform-surfaces.md](references/platform-surfaces.md) for the authored file layout and install targets. Read [invocation-posture.md](references/invocation-posture.md) before writing or tuning descriptions.

## Validate

Run in order:

1. `npm run build`
2. `npm test`
3. `uv run python "$ALM_DIR/scripts/quick_validate_agent.py" agents/`

The agent-specific validator checks cross-surface alignment, archetype-capability consistency, runtime defaults, and tools alignment. Fix structural issues before deeper evaluation.

When validating this skill package itself (not a target agent), use the canonical repo source only:

```
uv run python "$ALM_CANONICAL_DIR/scripts/quick_validate.py" "$ALM_CANONICAL_DIR"
uv run python "$ALM_CANONICAL_DIR/scripts/validate_eval_suite.py" "$ALM_EVAL_FILE"
```

## Evaluate

Use realistic prompts, not toy examples. Mix: `should-handle`, `should-stretch`, `should-not-handle`, `near-miss`.

Read [evaluation-loop.md](references/evaluation-loop.md) for the eval harness commands and benchmark setup.

## Optimize Invocation

Only when triggering is wrong. Draft `should-trigger` / `should-not-trigger` prompts, tighten descriptions, record before/after.

## Install

```
npm run install-agent --  --platform claude|codex|all --scope project
```

Validate before installing. Confirm installed copies exist under `.claude/agents/` and/or `.codex/agents/`.

## Audit

```
uv run python "$ALM_DIR/scripts/audit_agent_inventory.py" --root agents
```

Read [audit-rubric.md](references/audit-rubric.md) for the 11-dimension rubric and scoring formula. Prioritize dangerous overreach and structural breakage before polish.

## Close

After any stage, report: what was done, what changed, what was validated vs not, and the next step if work remains.

## Script Paths

- **Runtime**: `ALM_DIR=skills/agent-lifecycle-manager` (canonical), `.agents/skills/agent-lifecycle-manager` (Codex), `.claude/skills/agent-lifecycle-manager` (Claude Code)
- **Self-validation**: always use `ALM_CANONICAL_DIR=skills/agent-lifecycle-manager` and `ALM_EVAL_FILE=skills/agent-lifecycle-manager/eval/eval-cases.json`

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [liqiongyu](https://github.com/liqiongyu)
- **Source:** [liqiongyu/my-agents](https://github.com/liqiongyu/my-agents)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-liqiongyu-my-agents-agent-lifecycle-manager
- Seller: https://agentstack.voostack.com/s/liqiongyu
- Browse the marketplace: https://agentstack.voostack.com/browse

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