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interview — Claude Code skill: what it does, how to install

Guides founders through a structured six-slot interview to generate an agent build sheet and evaluation plan without requiring an API key.

Install into Claude Code · Plugin marketplace All methods and platforms ↓
/plugin marketplace add alirezarezvani/claude-skills
/plugin install agent-launcher-skills@claude-code-skills
Open on GitHub

What interview does

The skill manages phase one of constructing a Claude Managed Agent. It questions the creator across six core dimensions: job, trigger, inputs, actions, definition of done, and recurrence. The workflow focuses strictly on a single core responsibility for v0, while real MCP connectors and irreversible actions become deferred backlog items.

Under the hood, the workflow relies on three Python utilities. First, interview_planner.py translates user input into a primitives skeleton. Next, build_sheet_builder.py normalizes and assembles build-sheet.json. Finally, primitives_validator.py verifies platform limits with PASS, WARN, or FAIL outcomes. A FAIL status halts progress until issues are resolved. Python 3 is required to run the planning scripts.

What it helps with

  • scope the core job of a new Claude Managed Agent
  • create a validated build-sheet.json specification
  • establish measurable rubrics and completion criteria
  • separate v0 essentials from deferred v1 and v2 capabilities

Example prompts for the agent

  • Help me scope an agent for triaging support emails
  • I have an idea for an agent, let us map it out
  • What should this agent do and how do we structure it?

How to install interview

1Plugin marketplace

/plugin marketplace add alirezarezvani/claude-skills
/plugin install agent-launcher-skills@claude-code-skills

This installs the whole agent-launcher-skills plugin with all its skills

2Skills CLI (Vercel)

npx skills add alirezarezvani/claude-skills --skill interview -a claude-code

3Manually: put the files in place

~/.claude/skills/interview/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/interview/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about interview

How to install interview in Claude Code?

First add the marketplace repository by running /plugin marketplace add alirezarezvani/claude-skills, then install the package with /plugin install agent-launcher-skills@claude-code-skills.

What does the interview skill produce?

It outputs a normalized build-sheet.json artifact containing primitives mapping, evaluation rubrics, and explicit deferrals for subsequent stages.

Is an API key required during the interview?

No, this scoping stage works completely without an API key because its sole purpose is generating the architectural specification.

Source text

SKILL.md · MIT
---
name: interview
description: 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 table + v1/v2 deferrals + eval plan) WITHOUT needing their API key yet. Use when the user says "help me scope an agent", "I have an idea for an agent", "what should this agent be", or when the orchestrator routes phase=interview. Drives the six intake slots (job, trigger, inputs, actions, definition-of-done, recurrence) via AskUserQuestion, maps them to primitives with interview_planner.py, assembles build-sheet.json with build_sheet_builder.py, and validates limits with primitives_validator.py. Connectors are mockable in v0 (schema-true custom tools); real MCP servers become v1 deferrals. Distinct from stage-launch (which turns the sheet into payloads).
license: MIT
metadata:
  version: 2.11.2
  author: Alireza Rezvani
  tags: [cma, interview, scoping, build-sheet, primitives, deferrals, eval-plan]
  compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]
---

# Phase 1 — Interview → Plan

Open warmly with one or two examples from
[`../../references/examples-bank.md`](../../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`](../../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.**
   ```bash
   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.**
   ```bash
   python3 scripts/build_sheet_builder.py --plan ./my-agent/plan.json --out-dir ./my-agent
   ```
4. **Validate limits.**
   ```bash
   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).

© Alireza Rezvani · MIT · alirezarezvani/claude-skills

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