claude-skills/docs/skills/agent-launcher/interview.md

title	description
Phase 1 — Interview → Plan — Agent Skill for Claude Managed Agents	Phase 1 of building a Claude Managed Agent — interview the founder about the one job the agent should do, then produce a build sheet (CMA primitives. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw.

Phase 1 — Interview → Plan

:material-rocket-launch-outline: Agent Launcher :material-identifier: `interview` :material-github: Source

Install: claude /plugin install agent-launcher-skills

Open warmly with one or two examples from [references/examples-bank.md](https://github.com/alirezarezvani/claude-skills/tree/main/agent-launcher/references/examples-bank.md), then interview the founder into a build sheet. No API key needed in this phase — the output is a plan.

The six intake slots (ask one at a time; use AskUserQuestion for choices)

Slot	Question	Maps to
Job	"What one job should this agent do end-to-end?"	agent.system + outcome description
Trigger	"What kicks it off — you ask it, an event, or a schedule?"	on-demand / event / cron
Inputs	"What does it read?" (files, repo, memory, gmail/slack/github, web)	resources / MCP servers / memory
Actions	"What does it do?" (draft, write, call APIs, run code)	agent toolset / custom tools / MCP
Done	"How would you grade a good run?"	outcome rubric (required)
Recurrence	"Once, on request, or on a cadence?"	single-pass / grade-loop / cron-loop

See [references/interview-to-config.md](https://github.com/alirezarezvani/claude-skills/tree/main/agent-launcher/references/interview-to-config.md) for the full mapping.

Workflow

1. Interview. Walk the six slots. Capture the founder's own words — never invent specifics they didn't claim.
2. Map to primitives.

   python3 scripts/interview_planner.py \
     --job "Triage overnight support email" --trigger schedule \
     --inputs "gmail,memory" --actions "label,reply" \
     --dod "one label per email, grounded reason, no invented facts" \
     --recurrence daily --out ./my-agent/plan.json
   

   MCP inputs become schema-true mock custom tools in v0 and a v1 deferral to wire the real server. Irreversible actions (send/publish) become v2 deferrals behind always_ask.
3. Assemble the sheet.

   python3 scripts/build_sheet_builder.py --plan ./my-agent/plan.json --out-dir ./my-agent
   

4. Validate limits.

   python3 scripts/primitives_validator.py --sheet ./my-agent/build-sheet.json
   

   FAIL blocks progress; fix and re-run. WARN is advisory (surface it).
5. Record the plan in the goal. goal_state.py set --phase stage-launch --artifact build_sheet=./my-agent/build-sheet.json, then advance.

Hard rules

• v0 is the core job only. Everything else is a versioned deferral with a reason and an exact mechanism.
• Their problem, their words.
• No key yet. The interview produces a plan; the key is a Phase-2 concern.

Forcing-question library (recommend + cite)

1. "What one job — singular?" Recommend: the most-repeated task. Cite: interview-to-config.md. Two jobs → two agents.
2. "Real integration or v0 mock?" Recommend: mock; wire MCP as v1. Cite: interview-to-config.md rule 1.
3. "How do you grade it?" Recommend: 3–5 grounded rubric lines. Cite: cma-primitives.md (rubric required).
4. "Smarter over time?" Recommend: attach memory only if yes. Cite: cma-primitives.md (memory limits + injection).
5. "Once, or on a cadence?" Recommend: on-demand v0, schedule as Phase-4. Cite: loops-and-workflows.md.

Tools

• scripts/interview_planner.py — answers → primitives skeleton + deferrals.
• scripts/build_sheet_builder.py — assemble/normalize build-sheet.json.
• scripts/primitives_validator.py — validate vs CMA limits (PASS/WARN/FAIL).