autopilot-interview

name	autopilot-interview
description	Use when stress-testing, speccing, or refining a plan; or when the user asks to be grilled or interviewed in detail about technical implementation, UI/UX, concerns, tradeoffs, scope, rollout, or risks.

Autopilot Interview

Interview a plan by default through deep auto-interviewing with selective autonomy. Build a broad question map, resolve ordinary questions yourself, and stop for human judgment when an answer would materially change direction, risk, cost, UX, architecture, or the final spec/plan.

When the user asks to be interviewed or grilled in detail, use the same default workflow at full intensity: surface non-obvious questions across product, technical implementation, UI/UX, concerns, tradeoffs, risks, rollout, and acceptance criteria until the requested spec, plan, or next artifact is complete enough to write.

Start

1. Find the plan in the conversation, repo, issue, PRD, or named file. If none is clear, ask what to interview.

2. Capture the completion target if the user gave one: write a spec to a file, produce an implementation plan, proceed to implementation, or return a resolved plan in chat.

3. When file writes are allowed, create a scratch decision log:

   node <this-skill-dir>/scripts/new-autopilot-interview-run.mjs "short plan title" --root .
   

   If the script is unavailable, manually create .workflow/autopilot-interview/<timestamp>-<slug>/decision-log.md and ensure .workflow/ is locally ignored. If the active host mode forbids file writes, keep the same context capsule and decision ledger in chat until writes are allowed.

4. Keep the log current after every decision. Update the context capsule near the top so the session can recover after compaction.

Default Auto-Interview

Use this for every interview, spec, plan refinement, or stress-test. For quick stress-tests, still build the map internally but ask only the highest-stakes questions. For explicit interview requests, run the map at full intensity.

Before asking questions, build a question map across all relevant domains:

• Product promise, target users, jobs-to-be-done, scope boundaries, and non-goals.
• Technical implementation, architecture, ownership boundaries, data model, APIs, schemas, migrations, compatibility, and dependencies.
• UI/UX, navigation, core flows, edge flows, empty/loading/error states, permissions, responsiveness, accessibility, and copy tone.
• Concerns, tradeoffs, risks, security, privacy, abuse cases, observability, operations, rollout, and support.
• Testing, acceptance criteria, success metrics, performance, failure modes, and documentation.

Question quality rules:

• Ask non-obvious questions whose answers change the shape of the spec, plan, UI, architecture, risk, or cost.
• Convert obvious questions into sharper hidden-fork questions. Prefer "which tradeoff should win?" over "do you want X?"
• Always provide a recommended answer first, with the rationale and the cost of the alternatives.
• Continue until every material domain is either decided, auto-decided, explicitly skipped, or recorded as an assumption.
• If the user said "then proceed to..." complete that target after the interview rather than stopping at the decision list.

Decision Loop

Repeat until no meaningful open questions remain:

1. Pick the most important unresolved question from the plan and auto-interview map, respecting dependencies.
2. If the repo, docs, code, schema, tests, or external primary source can answer it, explore and use that answer.
3. Classify the question:
   • auto: a two-way door with a valid smart answer: evidence-backed, convention-driven, easy to reverse, low-risk, or implementation-local.
   • human: a one-way door: hard to reverse, expensive to unwind, preference-defining, or likely to shape product direction, architecture, cost, risk, or user promise.
   • skip: cosmetic, premature, or unlikely to change the plan.
4. For auto, choose the recommendation yourself and record it.
5. For human, ask exactly one question with 2-3 concrete options, put the recommended option first, and wait. Use the host's structured ask-user mechanism when available.
6. Record the exact decision question, options, and answer before moving on.

Do not stop just because the current plan has no obvious holes. Re-scan the auto-interview map for hidden forks, edge states, and downstream tradeoffs before ending.

Escalation Rule

Use one-way door vs. two-way door judgment.

Auto-decide when all are true:

• There is a valid smart answer.
• The answer is easy to change later.
• A wrong answer would not waste much implementation effort.
• The choice does not lock product, architecture, data, security, cost, rollout, or user promise.

Ask the user when any are true:

• The decision is hard to reverse or expensive to unwind.
• The choice would commit product or system direction in a way that is hard to reverse, such as a public API, migration, dependency, security posture, billing model, or rollout path.
• Reasonable strong teams would choose differently and downstream work depends on the answer.

When unsure, ask: "If this is wrong, can we change it cheaply after implementation starts?" If yes, auto. If no, ask.

Question Format

For human questions:

Question: <one concrete decision>

A. <recommended option> (Recommended) - <one-line reason>
B. <real alternative> - <tradeoff>
C. <real alternative, if useful> - <tradeoff>

Do not ask bundled questions. If two choices are dependent, ask the upstream one first.

When recording a human decision, copy the Question: line and the option labels exactly as shown to the user.

Log Format

Append after every decision:

### Decision N: <short decision topic>

- Mode: auto | human
- Question asked: <exact human prompt or internal decision question>
- Options presented: <A/B/C options shown, or "not presented; auto-decided">
- Chosen answer: <A/B/C plus option label, or short answer>
- Reason: <one-line rationale>
- Evidence: <repo path, command, source, or "user answer">
- Downstream implications: <what this unlocks or changes>

Maintain the context capsule:

• Goal
• Current state
• Constraints
• Completion target
• Accepted decisions
• Open high-stakes questions
• Assumptions and defaults

Stop

Stop when remaining questions are trivial, cosmetic, or would not change the resolved plan, spec, UI, architecture, risk profile, or implementation path.

If the user requested a follow-on target, complete it:

• Spec target: write the resolved spec to the requested file, or choose a conventional project path if obvious.
• Planning target: produce the implementation plan with decisions baked in.
• Implementation target: proceed only if the remaining work is clear and allowed in the active host mode.

Otherwise end with:

• Decisions: grouped into auto and human.
• Resolved plan: rewritten with decisions baked in.
• Overrides: specific decisions the user can flip, plus which downstream decisions would need re-resolution.

Do not invent a plan. Do not keep interviewing after decisions stop adding value.