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Found 87 Skills
Use when you need to execute I2 (Implementation Execution) in the Spec Pack of sdlc-dev, using `{FEATURE_DIR}/implementation/plan.md` as the sole SSOT to implement in batches, run minimal validation, write back audit information, and report at batch checkpoints; stop immediately when encountering blocks or clarification items.
AI SDLC repository spec-driven development workflow. Use when an AI assistant receives a medium or large feature, refactor, API change, architecture change, provider integration change, or any request that must follow requirements, design, test cases, QA planning, tasks, implementation, and validation. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution.
Launch Loki Mode autonomous SDLC agent. Handles PRD-to-deployment with minimal human intervention. Invoke for multi-phase development tasks, bug fixing campaigns, or full product builds.
AI SDLC context-aware navigation workflow. Use when an AI assistant needs to determine what to do next, select the right installed skill, start or resume a feature, explain blockers, inspect available capabilities, or provide evidence-backed required and optional next actions from repository state. Supports `--quick-flow` for compact guidance and `--full-flow` for stricter context verification.
Use when you need to execute I1 (Implementation Plan) in the Spec Pack of sdlc-dev, convert requirements/design into `{FEATURE_DIR}/implementation/plan.md` (the single source of truth (SSOT) for execution checklist and status), and provide an unambiguous task list for subsequent I2 execution.
Portable AI SDLC shared-helper runtime. Use when an AI assistant installs, verifies, diagnoses, or repairs project-scoped AI SDLC skills whose deterministic scripts depend on shared state, artifact, context, path, TOON, migration, or index modules. This is an installation dependency, not a lifecycle entry point.
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`.
AI SDLC business analysis workflow. Use when an AI assistant needs to frame a feature or change before implementation, derive actors, workflows, business rules, assumptions, acceptance criteria, and richer spec context for requirements and design. 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.
Optional AI SDLC user-experience workflow. Use when an AI assistant needs to define actors, goals, user journeys, interaction steps, loading/empty/error/success states, recovery behavior, content intent, accessibility requirements, or UX acceptance evidence and route them into traceable human and machine artifacts. Supports `--quick-flow` for a focused journey slice and `--full-flow` for strict state, accessibility, and acceptance coverage.
AI SDLC versioned policy-as-code workflow. Use when an AI assistant needs to resolve layered delivery policy, evaluate an action with explainable rules and gates, protect organization minimums from weaker overrides, apply or reject an expiring waiver, or select a reusable assurance profile. Supports `--quick-flow` for deterministic evaluation and `--full-flow` for strict owner and exception review.
Orchestrates multiple skills to achieve high-level goals. Acts as the brain of the ecosystem to coordinate complex workflows across the SDLC.