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interview

Interview you one question at a time, each choice with a recommendation, to settle a big outcome before agents work alone

Install / Use

npx skills add boshu2/agentops --skill interview

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

88/100

Category

Legal

Supported Platforms

Universal

Our assessment of interview

interview scores 88/100 on our quality scale, 83rd of 212 Legal skills we index (top 40%).

Its SKILL.md is 7.4 KB long, well organised into 9 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.

It has 445 GitHub stars, a meaningful sign that others use it.

Substance
29/30
Structure
18/20
Description
15/15
Adoption
11/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 35 days ago, so interview is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

interview compared with similar skills

All 4 of these similar skills score higher than interview; compare them before choosing.

SkillScoreStarsUpdatedFormat
interview (this skill)by boshu28844535d agoSKILL.md
Agent-Reachby Panniantong100105.5k3d agoCLAUDE.md
taste-skillby Leonxlnx100104.3ktodayCLAUDE.md
headroomby headroomlabs-ai10078.1ktodayCLAUDE.md
Scraplingby D4Vinci10090.2ktodayMCP Server

Frequently asked questions

How do I install interview?
Run npx skills add boshu2/agentops --skill interview. The install tabs above show the steps for each supported agent.
Which AI agents does interview work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is interview safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is interview still maintained?
The repository was last updated 35 days ago, so interview is actively maintained.

name: interview description: 'Interview you one question at a time, each choice with a recommendation, to settle a big outcome before agents work alone. Use when: asked to interview you about a goal or plan.' practices: [bdd-gherkin, ddd-bounded-context, design-by-contract] hexagonal_role: domain consumes: [repo-context, native-work-state] produces: [caller-outcome, goal-acceptance] context_rel:

  • kind: supplier-to with: craft-goal skill_api_version: 1 user-invocable: true metadata: tier: execution dependencies: [] capabilities: [interview_caller, settle_caller_choices, write_acceptance_examples, settle_domain_terms] effects: [update_intent_source] canonical_status: canonical disposition: keep_strategy stability: stable output_contract: 'one question per turn with a labeled recommendation and tradeoff on each choice question; decided, terms, open and deferred lists the caller can see; settled decisions appended to the existing intent source within authority; a handoff to Craft Goal, RPI or Plan'

Interview

Shape a big outcome with the caller, one question per turn, before agents run alone: you look up facts; the caller makes choices and supplies what only they know. Interview creates nothing new (no goal, bead or file), changes no status, claim or closure, and only appends notes to an existing intent source (Show the state). To test a plan, design or decision the caller already holds, see a held plan.

Each turn

  1. Look it up in the tracker, docs and code first. Ask the caller only for choices (outcome, proof, non-goals, authority, budgets, priorities, risk tolerance) and for facts no source holds: what they tried or ruled out, their outside systems, what their users already do. Ask such a fact openly, with no recommendation, before the choices that rest on it. If the caller contradicts a source, cite both and ask whether the source is stale or the caller wants a change.
  2. Pick the branch. Start with the outcome, then the open branch that most changes acceptance, scope or authority whose prerequisites are settled. Keep dependent choices open rather than inventing their prerequisites. After each answer, reconsider which choice can now be settled; a changed parent decision reopens only the answers that rely on it. Defer branches that cannot change the next action, with a condition for returning to them.
  3. Ask one question in this shape, so the caller can accept, amend or reject in one line; a fact question omits the recommendation and tradeoff. Wait for the answer.
  4. Record only what the caller decides, and a fact they supply as their report, not a decision. A skip stays open; "your call" accepts the recommendation shown.
Settled: <what the last answer decided, or nothing yet>. Open: <count>.
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>

Because "your call" turns the recommendation into scope, recommend only what the outcome needs. Add a criterion, safeguard, authority or budget the caller did not name only when the outcome fails without it or harm would land before anyone notices. Offer anything else costly to add later (stored data, a published interface, money, security) as an option, not as the recommendation. Never narrow what the caller asked for. Draw budget and authority options from a source (prior goals, the tracker, the caller's words); with none, ask openly.

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 accepts or amends its answers in one pass before anything is recorded, and authority, budgets and acceptance changes stay the caller's. Fact questions stay with the caller in this mode; the council answers only choices. If only another person can answer, keep the choice Open and offer a questionnaire for that person. The caller sends it; Interview contacts no one.

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

Show these lists on request, after a revision and at stop:

  • Decided: each choice; acceptance carries its Given/When/Then and proof. A fact the caller supplied appears here labeled as their report.
  • 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.

Number each choice Q<n> when first listed. As an item changes, Open and Deferred included, append its line to the intent source (root epic, issue or conversation) if the request or existing authorization covers editing it (the conversation always does); otherwise show it for the caller to append. The last line per Q<n> or term is current. Before treating acceptance as frozen by a running goal, confirm its current state from the native goal runtime or the caller. A saved Navigate checkpoint or open child build beads alone do not establish a running goal. If that state is unknown and matters to the proposed update, ask. While a goal runs, append no changed criterion or term; list it under Open in the conversation as an acceptance change for the caller to hold and re-craft. In BD:

bd context --json    # confirm the destination before any write
bd show <epic-id>    # on resume: the last line per Q<n> or term; start from Open
bd update <epic-id> --append-notes "decided Q<n>: <choice> | example: <Given/When/Then> | proof: <evidence>"
# or: "fact Q<n>: <report>" "term: <word> = <definition>" "open Q<n>: <choice>" "deferred Q<n>: <choice> | revive when <condition>"

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 (not when testing a held plan), or everything Craft Goal admission needs is settled:

  1. outcome, and non-goals the caller named or rejected;
  2. terminal acceptance, each criterion with its proving evidence;
  3. authority: reads, writes, external effects, Git, and when agents must ask;
  4. numeric wave and goal budgets and the HOLD threshold;
  5. the first falsifiable question.

While the caller is still here, test the settled answers once. Then 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.

Related Skills

View on GitHub
GitHub Stars445
CategoryLegal
Updated1mo ago
Forks41

Languages

Go

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions