Interview
SkillAI & modelsInterview the caller one question at a time to settle a big outcome before agents work alone. Use when: shaping a goal or large RPI. Not for one question on one slice; use Plan.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Interview skill
What this skill tells your AI
The instructions your AI receives, as published by boshu2/agentops in skills/interview/SKILL.md and read by ahel’s review.
Shape a big outcome with the caller, one question per turn, before agents run alone. You look up facts; the caller makes choices. Why: answering shapes the caller's thinking, and control is highest before launch. Interview creates no goal, bead or file and changes no status, claim or closure.
Each turn
- Look it up in the tracker, docs and code first. Ask only for choices: outcome, proof, non-goals, authority, budgets, priorities, risk tolerance.
- Pick the branch. Start with the outcome, then the open branch that most changes acceptance, scope or authority. Defer any that change no decision.
- Ask one question in this shape, so the caller can accept, amend or reject in one line. Wait for the answer.
- Record only what the caller decides. A skip stays open; "your call" accepts the recommendation shown. A revision reopens dependent answers.
Q<n>: <the decision>. <the question, with 2 to 4 options when they exist>
My recommendation: <answer>, because <source or reason>.
Tradeoff: <the one cost that matters>
Answerer
The caller answers by default. On request ("let a council answer my interview"), a council answers through Council's interview-panel mode. The caller still accepts or amends those answers in one pass before anything is recorded; authority, budgets and acceptance changes stay the caller's.
BDD: acceptance as examples
Drive each criterion to a Given/When/Then with an observable result and its proving evidence. Draft the example yourself as the recommendation; the caller accepts or edits it. "Works reliably" is not acceptance; ask what would be seen.
Given a Job has already completed
When the worker receives that Job again
Then it returns the completed result without a second side effect
# Proof: a redelivery test asserts one side effect and the completed result
DDD: one term per concept
When a word is vague, overloaded or has synonyms, ask which term the domain uses. Record one term with a one-line definition and use only it in examples, notes, code and tests. Domain owns deeper modeling.
Show the state
Open each turn with one line: what just settled and how many choices stay open. Show these lists on request, after a revision and at stop:
- Decided: each choice; acceptance carries its Given/When/Then and proof.
- Terms: each settled term with its one-line definition.
- Open: unanswered choices, most consequential first.
- Deferred: choices that change no next decision, and what revives them.
Within authority, append settled decisions and terms to the intent source (root epic, issue or conversation), and Open and Deferred at stop. If a goal already runs on that epic, do not append a changed criterion or term; list it under Open as an acceptance change so the caller can hold and re-craft first. In BD:
bd context --json # confirm the destination before any write
bd show <epic-id> # on resume: reuse settled notes, start from Open
bd update <epic-id> --append-notes "decided: <choice> | example: <Given/When/Then>"
Stop and hand off
Stop when the caller stops, the next question would only restate a settled answer, the work proves to be one slice, or Craft Goal admission is decided:
- outcome and non-goals;
- terminal acceptance, each criterion with its proving evidence;
- authority: reads, writes, external effects, Git, and when agents must ask;
- numeric wave and hard budgets, and the no-ratchet count that triggers HOLD;
- the first falsifiable question.
Hand over the lists; the caller starts the next step: Craft Goal for several related experiments, RPI or Plan for one outcome with items 1 to 3 and real bounds. Open items stay open; never fill one to finish.
Signals
- GitHub stars
- 446
- Forks
- 42
- Last commit
- Oct 2026
Others that do the same job
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- Key
interview-boshu2- Source
- github.com/boshu2/agentops
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