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Found 1,115 Skills
AI SDLC QA workflow. Use when an AI assistant is asked for QA planning, acceptance validation, regression scope, exploratory checks, smoke tests, release verification, or change-focused manual validation evidence. 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.
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.
Use when stories and clarified delivery context are ready and you need to produce a structured delivery specification that engineering and cross-functional teams can use for implementation planning and handoff. 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.
Amend an existing plan file — add tasks, modify pending or delegated tasks, and mark completed tasks that are invalidated by the change as [>] (needs re-run). Walks through analysis, cascading impact, and user confirmation before touching the file. When memory (wiki substrate) exists, it may also preserve durable amendment findings there. Reports goal impact and routes intent, boundaries, or validation changes to loam::setting-goals.
Build worlds through cascading consequences from speculative changes. Use when introducing new technologies, species, or alternate histories and need to trace realistic societal transformations across multiple domains.
Expert texture artist specializing in PBR workflows, Substance suite, Quixel Mixer, and hand-painted techniques for games and film productionUse when "texture artist, PBR textures, Substance Painter, Substance Designer, Quixel Mixer, normal map, roughness map, metallic map, albedo texture, base color map, texture baking, bake normal, texel density, trim sheet, texture atlas, channel packing, material layering, wear and tear, edge wear, hand painted texture, stylized texture, UDIM workflow, height map vs normal, color ID map, material ID, texture seams, tiling texture, seamless texture, texture, pbr, substance-painter, substance-designer, quixel, megascans, normal-map, roughness, metallic, albedo, uv-mapping, baking, trim-sheet, material, hand-painted, stylized, photorealistic, game-art, 3d-art" mentioned.
Property-based testing with fast-check (TypeScript/JavaScript) and Hypothesis (Python). Generate test cases automatically, find edge cases, and test mathematical properties. Use when user mentions property-based testing, fast-check, Hypothesis, generating test data, QuickCheck-style testing, or finding edge cases automatically.
WHEN: User is building Go/Templ web apps, using templUI components, converting sites to Templ, or asking about templ syntax, Script() templates, HTMX/Alpine integration, or JavaScript in templ WHEN NOT: Non-Go projects, general web development without templ
Finds all REFACTOR markers in codebase, validates associated ADRs exist, identifies stale markers (30+ days old), and detects orphaned markers (no ADR reference). Use during status checks, before feature completion, or for refactor health audits. Triggers on "check refactor status", "marker health", "what's the status", or PROACTIVELY before marking features complete. Works with Python (.py), TypeScript (.ts), and JavaScript (.js) files using grep patterns to locate markers and validate against ADR files in docs/adr/ directories.
Skill for creating custom lint rules by leveraging the existing linter ecosystems of various programming languages. This is a linter designed for AI Agents rather than humans, and its error messages function as correction instruction prompts for AI. Create custom rules in the `lints/` directory using standard methods for each language, including Rust (dylint), TypeScript/JavaScript (ESLint), Python (pylint), Go (golangci-lint), etc. Use this skill in the following scenarios: (1) When you want AI to enforce project-specific coding rules; (2) When you want to create lint rules that output AI-readable correction instructions when violations occur; (3) When you want to enforce naming conventions, structural patterns, and consistency rules through AI-driven linting. Triggers: "Create a linter rule", "Add a lint rule", "Enforce this pattern", "AI linter", "Custom lint", "Code rules", "Naming rules", "Structural rules", "create a linter rule", "add a lint rule", "enforce this pattern", "AI linter".
Guide for building with the Ika TypeScript SDK (@ika.xyz/sdk) on Mysten Sui v2. Use when creating dWallets, signing cross-chain transactions, managing encryption keys, or integrating with the Ika network from TypeScript/JavaScript. Triggers on tasks involving @ika.xyz/sdk, dWallet operations, IkaClient, IkaTransaction, or Ika cross-chain signing.