Identify ambiguities in feature specs and generate prioritized clarifying questions.
npx skills add https://github.com/jineyne/qt-mcp --skill speckit-clarify-jineyne
Please help me install this Agent Skill. Skill: speckit-clarify Source: https://github.com/jineyne/qt-mcp/tree/main/.claude/skills/speckit-clarify Command: npx skills add https://github.com/jineyne/qt-mcp --skill speckit-clarify-jineyne
Identify underspecified areas in the active feature specification by prompting up to 5 targeted clarification questions and recording answers back into the spec to reduce ambiguity and rework.
Run the speckit clarification workflow on the current feature spec to identify ambiguities and encode clarifications directly in the spec.
High-intent search queries and answers about installing and using this skill.
Identify ambiguities in your feature specification by generating up to 5 targeted clarifying questions prioritized by impact. Applying a taxonomy of functional scope, data model, and edge cases captures underspecified areas early in the planning phase to minimize downstream rework.
Track clarifications by embedding accepted answers into a dedicated Clarifications section within your feature specification. This ensures traceability by updating the spec with short, machine-parseable responses after each accepted answer during the workflow.
When a spec has multiple ambiguous categories, prioritization is driven by impact and uncertainty. The tool generates a prioritized question queue across data model, UX flow, non-functional attributes, integration, and constraints to guide the planning phase systematically.
Yes, the clarification workflow requires a spec-kit project structure. Pre-flight checks confirm the ability to load and modify the current FEATURE_SPEC before identifying spec gaps and generating targeted clarifications.
Answers must be short, machine-parseable responses. Once accepted, the tool updates the feature specification with these constrained answers in a dedicated Clarifications section to maintain structure and reduce ambiguity.
When defining software requirements, evaluate ambiguity across a taxonomy covering functional scope, data model, UX flow, non-functional attributes, integration, edge cases, and constraints to ensure comprehensive specification coverage.
ericstilesDetect underspecified areas in feature specifications and capture clarification questions.
intent-integrity-chainGenerate targeted clarifying questions for underspecified feature specs.
rcmilanGenerate targeted clarification questions for feature specs and encode answers back.
Asharf30Analyze feature documentation against a taxonomy and resolve ambiguities interactively.
