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Found 10,585 Skills
Design an auditable playbook when no narrower one fits: a large migration, an ambitious multi-part change, or work a human reviews after stepping away. Scales rigor to the task, runs a hypothesis loop, and logs decisions via show-me-your-work. Use for /figure-it-out, 'figure it out', a large migration, or when no narrower playbook applies.
shadcn-svelte (bits-ui) component integration for Inertia Rails Svelte (NOT SvelteKit): forms, dialogs, tables, toasts, dark mode, and more. Use when building UI with shadcn-svelte components in an Inertia + Svelte app or adapting shadcn-svelte examples from SvelteKit. Wire shadcn-svelte inputs to Inertia Form via name attribute and {#snippet} syntax. Flash toasts require Rails flash_keys initializer config.
College Basketball (CBB) data via ESPN public endpoints — scores, standings, rosters, schedules, game summaries, play-by-play, win probability, rankings, futures, team/player stats, and news for NCAA Division I men's basketball. Zero config, no API keys. Use when: user asks about college basketball scores, March Madness, NCAA tournament, standings, rankings, team rosters, schedules, play-by-play, betting futures, team/player statistics, or CBB news. Don't use when: user asks about NBA/WNBA (use nba-data/wnba-data), college football (use cfb-data), or non-sports topics.
Provides UI/UX design, user research, visual design, and brand consistency capabilities. Use this when you need to design interfaces, conduct user research, or create visual assets.
Use this whenever an OpenChoreo task needs a platform-level change or investigation: cluster setup, Helm upgrades, kubectl work, plane connectivity, platform resources, ComponentTypes, Traits, Workflows, gateways, secret stores, identity, GitOps, observability, or cluster-side debugging. If the same task also involves deploying or debugging an application through `occ`, activate `openchoreo-developer` too instead of waiting to escalate later.
Structured UX evaluation that produces quantitative assessments, identifies specific issues, and routes to the right Intent skill for resolution. Part of the Intent design strategy system. Runs heuristic evaluations, cognitive walkthroughs, anti-pattern detection, and task success analysis. Scores, categorizes, and prioritizes findings — then maps every issue to the skill that fixes it. Trigger on: UX review, design audit, heuristic evaluation, usability assessment, "review this design", "what's wrong with this", "evaluate the experience", "is this accessible", "check for dark patterns", "how good is this UX", "rate this design", "find the problems", or any request to systematically assess the quality of a user experience. This is the diagnostic entry point of the Intent system — the UX doctor that diagnoses issues and refers to specialists.
Detects anemic domain models, validates and refactors them into rich domain models, and enforces tactical DDD patterns (Entities, Value Objects, Aggregates, Domain Services, Domain Events). Use when the user asks to validate, review, or check domain models or DDD code; detect anemia; refactor domain objects; improve encapsulation; or mentions terms like "anemic model", "rich domain", "aggregate", "value object", "domain event", "ubiquitous language", "is this good DDD", "does this follow DDD", or "check my domain". Do NOT use for module or service boundary design, architectural decomposition, strategic DDD context mapping, or code outside the domain layer (DTOs, controllers, infrastructure adapters).
Populate `<docs-dir>/features/<slug>.md` for one, several, or every undocumented feature area by dispatching up to 10 parallel subagents — one per feature. The agent docs directory is discovered from `AGENTS.md` — typically `agents-docs/` (the `setup-agentic-repository` default) but may be elsewhere if `--docs-dir` was used. Use whenever the user wants to document features, fill out feature docs, write up specific features (e.g. "document auth and billing"), document all undocumented features, or follow up on `find-features` discovery. This is the natural sequel to `find-features` — that skill identifies what is missing, this skill writes the docs in parallel.
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
Alchemy IaC framework for TypeScript. Use when the user mentions Alchemy, wants to set up infrastructure, deploy Cloudflare Workers, configure databases, KV, R2, queues, use bindings and secrets, set up dev mode, use framework adapters (Vite, Astro, React Router, SvelteKit, Nuxt, TanStack Start), create custom resources, or work with any Alchemy provider.
Apply when introducing a new internal API while old callers still exist. Migrate callers and delete the old API in the same wave instead of preserving compatibility layers.
Expert guidance for Swift Testing: test structure, #expect/#require macros, traits and tags, parameterized tests, test plans, parallel execution, async waiting patterns, and XCTest migration. Use when writing new Swift tests, modernizing XCTest suites, debugging flaky tests, or improving test quality and maintainability in Apple-platform or Swift server projects.