mcpbeat

Clarify Question Loop

agentlas-ai/clarify-question-loop

Use when a meta-agent request is too ambiguous to safely generate, package, publish, or adapt without one to five targeted questions.

920 tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
1165
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/agentlas-ai/Agentlas-OS --skill clarify-question-loop

The instruction itself

6 sections, as written by the author

Clarify Question Loop

Ask only questions that change the generated package, runtime adapter, safety

boundary, or public/private release decision.

For /hep-build creation or behavior-changing packaging, this is not a

substitute for the Builder Interview and Research Gate in

docs/builder-interview-research-gate.md. Run that gate first: ask an 8-12

question first batch, research similar agent repositories or comparables and

academic/professional theory, then use this clarify loop only for the remaining

narrow ambiguities.

Procedure

  • Classify the current best mode.
  • If single-agent vs team selection would change the package shape and the

independent ownership boundaries are unclear, ask before generation. The

first batch must include this plain-language question: "이 일을 한 명의

전문가가 처음부터 끝까지 맡으면 되나요, 아니면 조사/분석/검토처럼 여러

전문가가 나눠 맡고 마지막에 합쳐야 하나요?"

  • Follow up on role count, role-specific tools/permissions, whether outputs

must be synthesized, and whether artifacts are sequential dependencies or

independent parallel packets.

  • Identify missing facts that would change files or safety.
  • Ask one to five short questions, preferably three. If more than five

functional-quality questions remain, return to the Builder Interview and

Research Gate instead of pretending the package is ready.

  • Do not ask for secrets. Ask for secret names or setup boundaries instead.
  • After answers arrive, re-run mode classification if needed.
  • Generate or repair the package using the answers and list assumptions.

Budgets and stop rule (briefing interview engine)

This loop shares the briefing interview engine's contract

(agentlas_cloud/interview/): a question is only worth asking if the answer

would change execution, not just its phrasing. Respect the surface budget

(chat 3-5 in one batch, stormbreaker <= 8 across two batches, build 8-12 plus

follow-ups). 'decide later' is always a valid answer — record it as deferred,

never re-ask. When answers you auto-confirmed from code/memory reach three in a

row, the next question must go to the human.

Default Questions

  • Which runtime targets should be supported?
  • Is this local-only, private-team, public open-source, or marketplace output?
  • What tools, APIs, files, or services must it use?
  • What should count as success?
  • What must it never read, write, publish, or spend?
  • 이 일을 한 명의 전문가가 처음부터 끝까지 맡으면 되나요, 아니면

조사/분석/검토처럼 여러 전문가가 나눠 맡고 마지막에 합쳐야 하나요?

Plain-Language Question Rule

Never ask non-technical users to choose internal labels such as

single-agent, team-builder, ownership boundary, memory/context, synthesis,

or produces/consumes. Translate them before asking:

  • ownership boundary -> "누가 따로 맡아야 하는 일인지";
  • memory/context -> "각자 따로 기억해야 할 자료, 기준, 진행 상황";
  • tools/permissions -> "각자 써도 되는 계정, 파일, 웹사이트, 도구";
  • synthesis -> "마지막에 결과를 한데 모으는 일";
  • sequential dependency -> "앞 사람이 끝낸 결과를 다음 사람이 이어받는 순서".

If a question still sounds technical, split it into two shorter everyday

questions and give examples such as 조사, 분석, 검토, 승인.

Reference

See docs/clarify-question-loop.md.

How to use it

Copy the folder

Take agentlas-ai/clarify-question-loop from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.