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Found 1,610 Skills
Build clinically meaningful ValueSets using the property filter system of each code system: SNOMED CT (attribute relationships + hierarchy), LOINC (CLASS/CLASSTYPE/STATUS/ORDER_OBS), RxNorm (TTY + ingredient relationships), ICD-10-CM (parent hierarchy), and UCUM (physical quantity). Use when the user wants to define a ValueSet by clinical criteria rather than enumerating codes manually, or when they ask "give me all X codes" for a code system.
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".
Explains business financial terms and frameworks for engineering managers — produces term definitions (ARR, COGS, CAC, LTV, gross margin, burn rate, EBITDA, AARRR), translation formulas for making engineering work visible in business language, and a three-layer framework for building business credibility. Use when the user says "business terms," "EBITDA," "burn rate," "CAC," "LTV," "gross margin," "ARR," "how do I speak to business people," "I don't understand finance," "make the case for engineering work," "connect engineering to business outcomes," "talk to the P&L owner," or "business impact." Do NOT use when the user wants to connect engineering metrics (DORA, velocity) to business metrics — use developer-productivity instead.
Build serverless TypeScript functions on Zavu Cloud — declare agents + tools in code with defineAgent / defineTool, deploy with `zavu deploy`, debug with `zavu agents executions`. Use this skill whenever the user wants code-driven AI agents, custom tool handlers, or event-driven business logic.
Loads the full ***plain language reference into context: syntax, section types (definitions, implementation reqs, test reqs, functional specs, acceptance tests), concept notation, frontmatter (import/requires/required_concepts/exported_concepts), templates, linked resources, module model, and authoring best practices. Use whenever authoring, editing, reviewing, or debugging .plain files, or before invoking any other skill that reads or writes .plain content.
Guides Site Reliability Engineering—SLI/SLO and error budgets, reliability dashboards and burn-rate alerting, production readiness reviews, capacity planning for availability, toil reduction, dependency and failure-mode analysis, release reliability (canaries, rollback criteria), and service-owner incident mitigation tied to customer impact. Use when defining or operating SLOs, measuring error budget burn, improving service reliability, running PRRs before launch, planning scalable resilient capacity, or leading technical mitigation during outages—not for CI/CD pipeline implementation (devops), incident program and paging policy design (incident-management-engineer), cloud access and patch tickets (cloud-system-administrator), load-test profiling (performance-engineer), rollout cutover strategy (deployment-strategist), or greenfield cloud build-out (cloud-engineer).
Stellar standards, ecosystem, and reference. Covers SEPs (Stellar Ecosystem Proposals), CAPs (Core Advancement Proposals), and a quick map for picking the right standard for wallets, anchors, payments, deposits/withdrawals, federation, deep links, and KYC. Also bundles ecosystem references (DeFi protocols, dev tools, wallets, infra, community projects) and curated documentation links. Use when you need to know which SEP applies, or want a starting point for ecosystem integrations and official docs.
Query Catalog, database, and table metadata resources in Alibaba Cloud Data Lake Formation (DLF). Provides read-only queries via the DLF OpenAPI Python SDK, supporting listing and viewing Catalogs, databases, tables with their detailed information and Schema definitions. Use cases: "list available Catalogs", "list databases", "view table schema", "search tables", "search tables by name", "fuzzy search", "view DLF metadata", "what databases are in the data lake", "what columns does a table have", "find tables whose name contains xxx". This Skill only contains read-only operations — no create, modify, or delete operations.
QLC+ (Q Light Controller Plus) lighting software — workspace files (.qxw), scenes, chasers, sequences, collections, EFX, RGB matrices, fixture definitions (.qxf), Virtual Console, and timing calculations. Use this skill whenever the user is working with QLC+ workspace XML, creating/editing scenes/chasers/shows, debugging timing or crossfade issues, generating fixture definitions, setting up Virtual Console widgets (cue lists, solo frames, buttons, sliders), troubleshooting HTP/LTP conflicts, fixing corrupted .qxw files, configuring QLC+ plugins (DMX USB, Art-Net, MIDI, E1.31), or asking any question where QLC+ is the software being used. Also trigger for SpeedModes, FadeIn/Hold/Duration, FixtureVal, RunOrder, or QLC+ function types. Do NOT trigger for general DMX hardware questions without QLC+ context, fixture buying advice, DAW-only questions, or custom protocol implementations.
Build code-first notification workflows with @novu/framework. Use when defining workflows in TypeScript (Zod / JSON Schema / Class Validator), composing channel steps (email, SMS, push, chat, in-app) with action steps (delay, digest, custom), exposing Step Controls for non-technical teammates, rendering React/Vue/Svelte Email templates, hosting the Bridge Endpoint inside Next.js, Express, NestJS, Remix, Nuxt, SvelteKit, H3, or AWS Lambda, syncing to Novu Cloud via CLI / GitHub Actions, securing production with HMAC, or implementing translations, hydration, multi-channel orchestration, and LLM-powered notification logic in code.
Generic framework for converting external events (SMS, meetings, social mentions) into brain-ingestible signals. Define a transform function, register a webhook URL, and incoming events get processed through the brain pipeline.
Define a motion system with duration tokens, easing vocabulary, and reduced-motion handling for consistent animation across a product.