/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.
$ npx -y skills add agentlas-ai/Agentlas-OS --skill clarify-question-loop --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/clarify-question-loop
Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when a meta-agent request is too ambiguous to safely generate, package, publish, or adapt without one to five targeted questions.
SKILL.md
clarify-question-loop.SKILL.mdname: clarify-question-loop
description: "Use when a meta-agent request is too ambiguous to safely generate, package, publish, or adapt without one to five targeted questions."
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
1. Classify the current best mode. 2. 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?" 3. Follow up on role count, role-specific tools/permissions, whether outputs must be synthesized, and whether artifacts are sequential dependencies or independent parallel packets. 4. Identify missing facts that would change files or safety. 5. 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. 6. Do not ask for secrets. Ask for secret names or setup boundaries instead. 7. After answers arrive, re-run mode classification if needed. 8. 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`.
Read more
name: clarify-question-loop description: "Use when a meta-agent request is too ambiguous to safely generate, package, publish, or adapt without one to five targeted questions."
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
1. Classify the current best mode. 2. 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?" 3. Follow up on role count, role-specific tools/permissions, whether outputs must be synthesized, and whether artifacts are sequential dependencies or independent parallel packets. 4. Identify missing facts that would change files or safety. 5. 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. 6. Do not ask for secrets. Ask for secret names or setup boundaries instead. 7. After answers arrive, re-run mode classification if needed. 8. 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`.
Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.
Other skills on agentlas-os.
- /agentlas-core-engine-meta-agent
Use when creating a single Agentlas agent, creating a multi-agent team, or packaging an existing local/external agent into Agentlas architecture. Make sure to use this for /meta-agent requests.
Open skill - /hephaestus-build
Use when the user types /prompts:hep-build, mentions @Hephaestus for build work, asks to create a single Agentlas agent, create a multi-agent team, or package an existing local/external agent into Agentlas architecture.
Open skill - /hephaestus-cloud
Use when the user types /hep-cloud or asks to staff from THEIR OWN Agentlas cloud packages only. Cloud is one exact source scope; Network means Local + owner Cloud + public Hub.
Open skill - /hephaestus-network
Use when the user types $hephaestus-network or /hep-network, mentions @Hephaestus, or asks Agentlas to staff a durable goal from registered Local, owner Cloud, and public Hub agents or teams. The active host LLM staffs each turn; the exact roster remains goal-bound until
Open skill - /hephaestus-storm
Use when the user types /hep-storm, says @Hephaestus storm <goal>, or asks to drive a goal to verified completion through a force-robust Stormbreaker loop. Stormbreaker routes the goal to real Agentlas specialists, materializes a dependency-ordered pipeline fabric, and runs each
Open skill - /hephaestus-upload
Use when the user types $hephaestus-upload or /hep-upload, or asks to upload, publish, or list an Agentlas agent or team. Ask Cloud (private) vs Agentlas Hub (public) FIRST, then publish through the bundled Hephaestus gate.
Open skill

