rohitg00--ai-engineering-from-scratch/phases/14-agent-engineering/35-initialization-scripts/outputs/skill-init-script.md

name, description, version, phase, lesson, tags

name	description	version	phase	lesson	tags
init-script	Interview a project and emit a deterministic init_agent.py with five probes plus a CI workflow that refuses to launch the agent if any probe fails.	1.0.0	14	35	init probes ci workbench fail-loud

Given a repo, the agent product, and its dependency surface, produce a project-specific init script and CI wiring.

Produce:

1. tools/init_agent.py with these probes: runtime version, listed dependencies, test command resolvability, required env vars, state file freshness.
2. init_report.json schema documented next to the script. Each probe returns (name, status: pass|warn|fail, detail).
3. .github/workflows/agent-init.yml (or equivalent) that runs the script and blocks the agent job on any fail-severity probe.
4. A pre-task hook script the agent runtime can call before each session starts.
5. Documentation in docs/init.md listing every probe, its severity, and how to fix a failure.

Hard rejects:

• Probes that call out to the network without a timeout. Init must be fast and offline-safe.
• Probes that require LLM calls. Init is deterministic plumbing.
• A non-zero exit code that the wrapper swallows. Fail loud is the whole point.
• Probes that touch state without idempotency. Two runs in a row must produce identical reports modulo timestamp.

Refusal rules:

• If the project has no test command, refuse to ship the script. Add the gap to the workbench audit instead.
• If the env var list contains secrets the script will print, refuse and force redaction. Init reports should never carry secrets.
• If a probe takes longer than three seconds in a dry run, surface the timing finding before shipping. Long probes turn init into ceremony.

Output structure:

<repo>/
├── tools/
│   ├── init_agent.py
│   └── pre_task.sh
├── docs/
│   └── init.md
└── .github/
    └── workflows/
        └── agent-init.yml

End with "what to read next" pointing to:

• Lesson 36 for the per-task scope contract that uses the init report's repo_paths.
• Lesson 37 for the runtime feedback loop that consumes the resolved test command.
• Lesson 38 for the verification gate that depends on probes passing.