--- name: clarification-expert-1b47c8480fbb description: Clarify ambiguous requests by researching first, then asking only judgment calls; stop before implementation. --- # Clarification Expert ## When to use - The request is ambiguous, under-specified, or missing success criteria. - The user asks to “build a system”, “optimize”, “make it better”, or “how do I”. - Requirements conflict, or trade-offs are implicit. ## Quick start 1. Research first; don’t ask for discoverable facts. 2. Maintain a running snapshot (facts, decisions, open questions). 3. Ask only judgment calls: prefer 1 question, never exceed 3 per batch (use `request_user_input_tool` if available; otherwise use the Human input block). 4. Incorporate answers and repeat until no open questions remain. 5. Generate verbose beads, then stop (no implementation). ## Asking questions (tool-aware) - Maintain an ordered queue of open questions. - Ask questions in batches: prefer 1; use up to 3 only when the questions are independent (no ordering dependency). - If a tool named `request_user_input_tool` is available, use it (do not render the fallback Human input block). - Otherwise, render the fallback Human input block (below). - After receiving answers, update the Snapshot and refresh the open-question queue: - remove answered questions - append newly discovered open questions (including follow-ups triggered by the answers) - continue looping until the queue is empty ### Loop pseudocode ```text open_questions := initial judgment calls (ordered) answered_ids := set() while open_questions not empty: batch := take_next(open_questions, max=3, prefer=1) if tool_exists("request_user_input_tool"): tool_args := { questions: batch_to_tool_questions(batch) } raw := call request_user_input_tool(tool_args) resp := parse_json(raw) answers_by_id := resp.answers else: render fallback numbered block for batch answers_by_id := extract answers from user reply for q in batch: a := answers_by_id[q.id].answers (may be missing/empty) if a missing/empty and q still required: keep q in open_questions (re-ask; rephrase; same id) else: remove q from open_questions answered_ids.add(q.id) update Snapshot with facts/decisions from a followups := derive_followups(answers_by_id, Snapshot) using rules below enqueue followups: - if a follow-up blocks other questions, prepend it - otherwise append it - dedupe by id against open_questions and answered_ids ``` ### Follow-up derivation rules Only create a follow-up when it is a judgment call required to proceed. Apply these rules in order: - If an answer expands scope ("also", "while you’re at it", "and then"), add: "Is this in scope for this request?" with options include/exclude. - If an answer introduces a dependency ("depends on", "only if", "unless"), add: "Which condition should we assume?" (options if you can name them; otherwise free-form). - If an answer reveals competing priorities (speed vs safety, UX vs consistency, etc.), add: "Which should we prioritize?" with 2-3 explicit choices. - If an answer contains a user_note with multiple distinct requirements, split into multiple follow-up questions (but keep each question single-sentence). - If a follow-up would ask for a discoverable fact, do not ask it; instead, treat it as a research action and update Snapshot Facts after inspecting the repo. Follow-up hygiene: - Assign each follow-up a stable snake_case `id` derived from intent (not position), and keep the same id if you later re-ask it. - Choose `header` <= 12 chars (tight noun/verb), and keep the `question` single-sentence. - Prefer options when the space of answers is small; omit options for genuinely free-form prompts. ## `request_user_input_tool` (preferred) When available, ask questions via a tool call with up to 3 questions. ### Call shape - Provide `questions: [...]` with 1-3 items. - Each item must include: - `id`: stable snake_case identifier (used to map answers) - `header`: short UI label (12 chars or fewer) - `question`: single-sentence prompt - `options` (optional): 2-3 mutually exclusive choices - put the recommended option first and suffix its label with "(Recommended)" - only include an "Other" option if you explicitly want a free-form option - if the question is free-form, omit `options` entirely - If you need to re-ask the same conceptual question (rephrased), keep the same `id`. Example: ```json { "questions": [ { "id": "deploy_target", "header": "Deploy", "question": "Where should this ship first?", "options": [ { "label": "Staging (Recommended)", "description": "Validate safely before production." }, { "label": "Production", "description": "Ship directly to end users." } ] } ] } ``` ### Response shape The tool returns a JSON payload with an `answers` map keyed by question id: ```json { "answers": { "deploy_target": { "answers": ["Staging (Recommended)", "user_note: please also update the docs"] } } } ``` In some runtimes this arrives as a JSON-serialized string in the tool output content; parse it as JSON before reading `answers`. ### Answer handling - Treat each `answers[].answers` as user-provided strings. - In the TUI flow: - option questions typically return the selected option label, plus an optional `user_note: ...` - free-form questions return only the note (and may be empty if the user submits nothing) - If the question used options and you suffixed the recommended option label with ` (Recommended)`, the selected label may include that suffix; strip it when interpreting intent. - If an entry starts with `user_note:`, treat it as free-form context and mine it for facts/decisions/follow-ups. - If an answer is missing/empty for a question you still need, keep it in the queue and re-ask (possibly rephrased or with options). ## Snapshot template ``` Snapshot - Facts: - Decisions: - Open questions: ``` ## Human input block (fallback) If `request_user_input_tool` is not available, use this exact heading and numbered list: ``` CLARIFICATION EXPERT: HUMAN INPUT REQUIRED 1. ... 2. ... 3. ... ``` ## Guardrails - Never ask what the code can reveal; inspect the repo first. - Keep questions minimal and sequential. - After bead creation, hard-stop. ## Deliverable format - Snapshot. - Ask for answers (use `request_user_input_tool` if available; otherwise use the Human input block). - One-line Insights/Next Steps. ## Activation cues - "clarify" - "ambiguous" - "build a system" - "make it better" - "optimize this" - "how do I" - "unclear goal" - "conflicting requirements" --- Source attribution: David-Li0406 Original project: https://github.com/David-Li0406/meta-skill-evloving/blob/ca3a335628981df10c36e00cb9850df2c247ab9a/skill-flow/data/skills-refined-36k/skillsmp/clarification-expert/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. 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See the License for the specific language governing permissions and limitations under the License. # Mega AI Hub resource metadata Creator / publisher: David-Li0406 Original project: https://github.com/David-Li0406/meta-skill-evloving/blob/ca3a335628981df10c36e00cb9850df2c247ab9a/skill-flow/data/skills-refined-36k/skillsmp/clarification-expert/SKILL.md Attribution basis: Source repository record Fields of work: Operations, Project & Program Management, Sales Roles: Business Process Analyst, Customer Success Manager, Project Manager Specialties: Cross Platform Tools: Tool not specified Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: f2d444051bc4f9bab7c05ac0418501099e3ab585aab8402ea9a53df04001f3e7