「clarification」の検索結果

Diagnose whether an LLM classifier's validation-gate failure is GOLD-BOUND before spending on prompt revision or model changes. Use when: (1) a scoring pipeline over-predicts a label (precision low, recall high) and a prompt clarification is proposed to tighten it, (2) a pilot/validation gate fails and the fix candidates are prompt edits, (3) inter-rater agreement on the weak label was already low (κ < ~0.6). Core check: if gold POSITIVES share the exact feature the revision would exclude, no prompt can pass a gold-scored gate — recall craters while precision barely moves. Also documents the verified surgical-pilot design (single-section diff, tune/holdout split, pre-registered gate, perturbation check on untouched sections).

日本語の概要は準備中です。原文の説明を表示しています。

Use when frontend work needs to communicate data, action, state, permission, validation, or business-rule needs to backend teams without dictating endpoint design, field names, database shape, or implementation details; Chinese triggers include front-end and back-end requirements handover, back-end requirements, API requirements clarification, data requirements description.

日本語の概要は準備中です。原文の説明を表示しています。

Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.

日本語の概要は準備中です。原文の説明を表示しています。

Stress-test a plan, decision, or idea as a dependency-aware design tree. Use for grill-me requests, assumption audits, and decision clarification before implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.

日本語の概要は準備中です。原文の説明を表示しています。

Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.

日本語の概要は準備中です。原文の説明を表示しています。

[Code Quality] Use to validate a spec artifact's decisions with the user across three contexts — a freshly-authored Feature Spec (idea-to-spec), an existing canonical spec before PBI decomposition (spec-to-pbi), or a refined idea + §8 test-specs (idea-to-pbi deep mode). Detects the context, walks every applicable validation category, and runs an exhaustive but budget-bounded blocking clarification gate so every non-obvious or conflicting decision is confirmed before the artifact drives downstream work.

日本語の概要は準備中です。原文の説明を表示しています。

GStack office-hours method for early product ideas, startup demand checks, builder-mode brainstorming, narrow wedge selection, and pre-architecture clarification before plan review.

日本語の概要は準備中です。原文の説明を表示しています。

Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when creating RFQ (Request for Quotation) documents for software development projects to send to vendors. Use this skill when you have received vague requirements from clients and need to structure them into clear, comprehensive RFQs that enable vendors to provide accurate estimates. Supports Japanese (default) and English, with systematic requirements elicitation, clarification, and markdown-formatted output.

日本語の概要は準備中です。原文の説明を表示しています。

Structured 6-step procedure for improving, renovating, or rebuilding existing pipelines, individual project folders, documentation structures, or software stacks. Addressable as "pipeline optimizer" (for whole topic pipelines, e.g. a software, research, or game-dev pipeline) or "project-folder optimizer" (for individual project folders within a pipeline, e.g. a single software tool or paper project). Triggers on tasks like "improve pipeline X", "optimize the stack", "rebuild Y", "renovation", "pipeline refactoring", "clean up project folder", "improve folder structure", "unify conventions", "documentation consolidation", "integrate into existing system", or any substantial intervention in established structures. Delivers building-stock analysis, purpose clarification, ideal sketch, gap plan, empirical pain-point identification, and retests with fresh subagents. Prevents parallel standards, duplication, and pipeline breaks.

日本語の概要は準備中です。原文の説明を表示しています。

Use when an agent must decide whether to proceed autonomously, ask for clarification, request approval, or select an appropriate verification scope for a coding or documentation task

日本語の概要は準備中です。原文の説明を表示しています。

Use for explicit undergraduate data-science teaching, assignment guidance, concept clarification, method selection, or output interpretation. Do not activate merely because a task contains data or Python code.

日本語の概要は準備中です。原文の説明を表示しています。

ALWAYS use this skill whenever you would otherwise ask the user a question in free-form chat -- for clarifications, confirmations (especially destructive actions), missing parameters, multiple-choice decisions, or structured form input. Elicitations are routed through the Unique AI Platform UI via `unique-cli elicit create` + `elicit wait` (the default polling pattern) or a single supervised `unique-cli elicit ask` call (only when your agent instructions say your environment supervises the wait) so the user gets a proper structured prompt and you get a structured answer back. Do NOT ask the user in plain chat when you can use this skill instead.

日本語の概要は準備中です。原文の説明を表示しています。

Reply to an applicant for an employer's Otameshi Tenshoku listing: match the application against the listed requirements item by item on what the applicant actually stated, list the questions still open, and draft an invitation, a request for clarification, a hold notice or a decline that sticks to the listed conditions, keeps other applicants and internal notes out, and presents any new work or dates as a proposal rather than an agreed term. Use when a hiring manager, recruiter or small-business owner has applications to answer, wants to know what to ask before inviting, or has to decline; do not use to judge an applicant's aptitude or predict hiring outcomes, to screen on personal attributes unrelated to the work, to design the work (trial-work-design) or the listing (trial-listing-draft), or to send the message or update applicant records on the user's behalf.

日本語の概要は準備中です。原文の説明を表示しています。

Write the executable feature specification — the WHAT and WHY artifact that agents and reviewers treat as source of truth. Owns both /specify and /clarify modes. Load when the user asks to write a feature spec, write a specification, write an executable spec, define functional requirements, capture acceptance criteria as Given/When/Then, or when the spec-driven-development orchestrator routes here. Also triggers on "feature spec", "executable spec", "/specify", "/clarify", "write the spec for this feature", "specification for", "spec-driven", "machine-readable spec". Output: docs/specs/YYYY-MM-DD-<slug>-feature-spec.md. Hard gate: cannot Approve while [NEEDS CLARIFICATION] markers remain.

日本語の概要は準備中です。原文の説明を表示しています。

在任何创意性工作前必须使用：创建功能、构建组件、增加能力或修改行为。通过自然对话挖掘需求，产出高质量验收标准（AC），为后续 TDD 开发提供测试依据。当用户说'我想做一个XX功能'、'帮我想想XX怎么做'、'我需要加一个XX'等模糊需求描述时触发。

日本語の概要は準備中です。原文の説明を表示しています。