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Found 9 Skills
Use this when you need to initialize a new Spec Pack in the AI SDLC workflow of this repository (create a three-digit numbered branch and the `.aisdlc/specs/{num}-{short-name}` directory), or when you are unsure about input parsing, short name rules, UTF-8 BOM file path parameter passing, script invocation methods, or output artifacts when executing `spec-init`.
Use after PRFAQ and BRD creation to run a strict final quality review, identify gaps or contradictions, and assign a readiness score before design or development starts. 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.
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.
AI SDLC code review workflow. Use when an AI assistant is asked to review a diff, PR, branch, commit, staged changes, or completed implementation against SDD requirements, tests, API contracts, security, and scope discipline. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution.
Use when goals, capabilities, and epics are defined and you need to decompose them into features, user stories, acceptance summaries, and cross-functional delivery tasks. 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.
AI SDLC Git-flow branching workflow. Use when an AI assistant starts implementation work, needs to create or verify a task branch, checks branch/spec alignment, or prepares to hand off a completed user-visible task to validation and commit prep. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution.
Use when stories, specs, BRDs, APIs, workflows, or equivalent delivery artifacts exist and you need to review them for testability, missing business rules, unclear behavior, scope ambiguity, and QA blocking gaps before generating tests. 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.
Use when the delivery gap review is complete and you need to convert a clarified initiative package into epics, user stories, acceptance criteria, scenario coverage, and priority signals tied to business value. 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.
Use when requirements are testable enough and you need to define QA scope, coverage priorities, test strategy, suite intent, test data needs, environment dependencies, and risk-based execution focus. 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.