AI Sdlc Working Backwards Discovery

About this skill

Use when a user needs a staged working-backwards interview to clarify the customer problem, audience, value proposition, business case, MVP, requirements, risks, and success metrics before any PRFAQ is written. Supports --quick-flow for fast assumption-driven execution and --full-flow for question-driven verified execution. Explicit full or end-to-end spec refinement requests continue through the existing 18-stage refinement cascade.

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Original listing metadata

Original name

ai-sdlc-working-backwards-discovery

Original description

Use when a user needs a staged working-backwards interview to clarify the customer problem, audience, value proposition, business case, MVP, requirements, risks, and success metrics before any PRFAQ is written. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution. Explicit full or end-to-end spec refinement requests continue through the existing 18-stage refinement cascade.

About this listing

Category: General
Reported license: Not specified
Listing language (estimated): English
Review status: Not individually reviewed
Agent compatibility: Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.