speckit.clarify

User Input

$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Outline

Goal: Detect and reduce ambiguity or missing decision points in the active feature specification and record the clarifications directly in the spec file.

Note: This clarification workflow is expected to run (and be completed) BEFORE invoking __SPECKIT_COMMAND_PLAN__. If the user explicitly states they are skipping clarification (e.g., exploratory spike), you may proceed, but must warn that downstream rework risk increases.

Execution steps:

1. Run {SCRIPT} from repo root once (combined --json --paths-only mode / -Json -PathsOnly). Parse minimal JSON payload fields:

   • FEATURE_DIR
   • FEATURE_SPEC
   • (Optionally capture IMPL_PLAN, TASKS for future chained flows.)
   • If JSON parsing fails, abort and instruct user to re-run __SPECKIT_COMMAND_SPECIFY__ or verify feature branch environment.
   • For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'''m Groot' (or double-quote if possible: "I'm Groot").

2. IF EXISTS: Load /memory/constitution.md for project principles and governance constraints.

3. Load the current spec file. Perform a structured ambiguity & coverage scan using this taxonomy. For each category, mark status: Clear / Partial / Missing. Produce an internal coverage map used for prioritization (do not output raw map unless no questions will be asked).

   Functional Scope & Behavior:

   • Core user goals & success criteria
   • Explicit out-of-scope declarations
   • User roles / personas differentiation

   Domain & Data Model:

   • Entities, attributes, relationships
   • Identity & uniqueness rules
   • Lifecycle/state transitions
   • Data volume / scale assumptions

   Interaction & UX Flow:

   • Critical user journeys / sequences
   • Error/empty/loading states
   • Accessibility or localization notes

   Non-Functional Quality Attributes:

   • Performance (latency, throughput targets)
   • Scalability (horizontal/vertical, limits)
   • Reliability & availability (uptime, recovery expectations)
   • Observability (logging, metrics, tracing signals)
   • Security & privacy (authN/Z, data protection, threat assumptions)
   • Compliance / regulatory constraints (if any)