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Found 82 Skills
Use after backlog decomposition to define prioritization, MVP and release slices, sequencing, readiness, traceability, and JIRA-ready outputs, then score backlog quality for planning and estimation. 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 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.
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.
Use when PRFAQ, BRD, PRD, product brief, workflow, or equivalent initiative artifacts exist and you need to review them for planning gaps, unclear scope, weak priorities, missing actors, and backlog-blocking ambiguity before decomposing work. 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 a PRFAQ, BRD, or equivalent discovery package exists and you need to review it for delivery gaps, contradictions, missing business rules, and insufficient implementation handoff detail before writing user stories or specs. 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.
Guided authoring of an architectural invariant catalog entry through a 6-step interview (elicit, locate, weight, enforce, number, commit). Drives the invariants_scaffold and invariants_add orchestrate verbs — the agent supplies judgment and natural-language elicitation; the verbs own schema validation, file writing, and event emission. Defaults to mode: audit; mode: check is an advanced opt-in. Triggers: 'add an invariant', 'author an invariant', 'enforce an architectural rule', or invariants. Do NOT use for: editing workflow state, running a review, or hand-writing YAML (the verbs write it — never emit catalog YAML yourself).
Review a development pipeline where AI coding agents write, commit and deploy — permission boundaries, approval gates on irreversible actions, credential scope, and what must never be delegated. Use when agents have write access to a repository or an environment.
Review Kanban handoffs and route verified outcomes.