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Found 1,261 Skills
Establish or formalize your design system foundation. Create design tokens (color, typography, spacing, shadows, borders), define component architecture, document design principles, and build the structure that enables consistency and scalability. Works with Tailwind CSS and framework-agnostic approaches.
OmniStudio FlexCard creation and validation with 130-point scoring. Use when building at-a-glance UI cards, configuring data source bindings to Integration Procedures, or reviewing existing FlexCard definitions for accessibility and performance. TRIGGER when: user creates FlexCards, configures data sources, designs card layouts, or asks about OmniUiCard metadata. DO NOT TRIGGER when: building OmniScripts (use omnistudio-omniscript-generate), creating Integration Procedures (use omnistudio-integration-procedure-generate), or analyzing dependencies (use omnistudio-dependencies-analyze).
Golang semantic code intelligence via `gopls`, the official Go language server — go-to-definition, find references, call/implementation hierarchy, workspace symbol search, package API discovery, diagnostics, safe rename, refactors (extract/inline/fill/rewrite code actions), formatting, and generated tests. Reaches an agent via gopls's own MCP server (`go_*` tools), Claude Code's native `LSP` tool, or the `gopls` CLI. Use when navigating or refactoring Go code — jumping to a definition, finding call sites before a rename, understanding a file's or package's dependencies, running diagnostics after an edit, or extracting/inlining/renaming. Not for the published ecosystem — packages not in your `go.mod`, versions, licenses, importers — → See `samber/cc-skills-golang@golang-pkg-go-dev` skill (`godig`). Not for a whole-tree vulnerability audit → See `samber/cc-skills-golang@golang-security` skill (`govulncheck`).
Pinia official Vue state management library, type-safe and extensible. Use when defining stores, working with state/getters/actions, or implementing store patterns in Vue apps.
Python type safety with type hints, generics, protocols, and strict type checking. Use when adding type annotations, implementing generic classes, defining structural interfaces, or configuring mypy/pyright.
OpenAPI (Swagger) 2.0 specification for describing REST APIs. Use when writing, validating, or interpreting Swagger 2.0 specs, generating clients/docs, or working with path/operation/parameter/response/schema/security definitions.
Interactive skill creation and import with automated validation and marketplace compliance. Use when: - "Create a new skill" - "Import an existing skill" - "Create a new agentic pack" - "Add skill to <pack>" - "Build skill for <rh-product>" - User mentions "skill builder", "contribute", "new skill", "import skill", or "new pack" Two modes: create from scratch or import existing SKILL.md. Guides through discovery, definition, generation, and validation. Enforces SKILL_DESIGN_PRINCIPLES.md and agentskills.io spec.
Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling
Define server-side JavaScript functions for Steedos objects using YAML. Functions are callable via REST API or from buttons/triggers. Covers function definition (.function.yml files in main/default/functions/), inline script with ctx/objects/global context, REST API exposure, calling from amis_button schemas, and examples for CRUD operations, data processing, and external API integration.
Create and manage writing personas with NNGroup 4-dimension tone framework (Funny-Serious, Formal-Casual, Respectful-Irreverent, Enthusiastic-Matter-of-fact). Personas define readability targets, sentence length distribution, vocabulary tier, contraction frequency, and summary box label. Used by blog-write and blog-rewrite to enforce consistent voice. Use when user says "persona", "voice", "tone", "writing style", "brand voice", "create persona", "use persona".
Run metric-driven iterative optimization loops. Define a measurable goal, build measurement scaffolding, then run parallel experiments that try many approaches, measure each against hard gates and/or LLM-as-judge quality scores, keep improvements, and converge toward the best solution. Use when optimizing clustering quality, search relevance, build performance, prompt quality, or any measurable outcome that benefits from systematic experimentation. Inspired by Karpathy's autoresearch, generalized for multi-file code changes and non-ML domains.
Generate personalized status briefings on demand. Pulls from your configured data sources (GitHub, email, Teams, Slack, and more), synthesizes across them, and drafts updates in your own communication style for any audience you define.