agentlas-core-engine-m…
Use when creating a single Agentlas agent, creating a multi-agent team, or packaging an existing local/external agent into…
Use when a meta-agent request is too ambiguous to safely generate, package, publish, or adapt without one to five targeted questions.
Claude Code
$ npx -y skills add agentlas-ai/Agentlas-OS --skill clarify-question-loop --agent claude-code
Codex
$ npx skills add agentlas-ai/Agentlas-OS --skill clarify-question-loop -a codex -y
Cursor
$ npx skills add agentlas-ai/Agentlas-OS --skill clarify-question-loop -a cursor -y
Gemini CLI
$ npx skills add agentlas-ai/Agentlas-OS --skill clarify-question-loop -a gemini-cli -y
GitHub Copilot
$ npx skills add agentlas-ai/Agentlas-OS --skill clarify-question-loop -a github-copilot -y
OpenCode
$ npx skills add agentlas-ai/Agentlas-OS --skill clarify-question-loop -a opencode -y
Windsurf
$ npx skills add agentlas-ai/Agentlas-OS --skill clarify-question-loop -a windsurf -y
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."
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 `contracts/builder-interview-research-gate.md`. Run that gate first: assess the supplied context and ask only material gaps, including zero questions when sufficient (8-12 only if that many gaps remain); research similar agent repositories or comparables and academic/professional theory, then use this clarify loop only for the remaining narrow ambiguities.
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.
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 asks only the material gaps). 'decide later' is always a valid answer — record it as deferred, never re-ask. Outside build, when answers you auto-confirmed from code/memory reach three in a row, the next question must go to the human.
조사/분석/검토처럼 여러 전문가가 나눠 맡고 마지막에 합쳐야 하나요?
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:
If a question still sounds technical, split it into two shorter everyday questions and give examples such as 조사, 분석, 검토, 승인.
See `docs/clarify-question-loop.md`.
An open-source AI agent OS inspired by OpenAI Dots, Meta Muse, Claude Duet, Nous Hermes, and Mem0. Built to lead entire projects rather than isolated prompts. Model-agnostic (BYOM) and native to Claude Code, Codex, Cursor, Antigravity, and Agentlas Desktop.
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