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Found 274 Skills
Generate professional, Outlook-compatible email templates (EML + HTML) through natural conversation. Creates pixel-perfect newsletter layouts, announcement emails, weekly reports, event invitations, and any formatted email that needs to render correctly in Outlook. MUST use this skill when the user wants to: create or design an email template, generate an EML file, make a newsletter, format an email for Outlook, design a 邮件模板, do 邮件排版 or 邮件设计, create HTML email with Outlook compatibility, build a professional-looking email to send via Outlook, or produce any kind of formatted/styled email output. Also trigger when the user mentions: weekly report email (周报邮件), product update email, event invitation email (活动邀请邮件), announcement email (公告邮件), company newsletter, or wants to make an email "look professional/beautiful" for sending. This skill handles the visual design and EML generation — not email sending, SMTP setup, or email parsing. Without this skill, Outlook emails will have broken layouts because Outlook uses Word's rendering engine which ignores modern CSS.
Integrate markstream-vue2 into a Vue 2 plus Vite app. Use when Codex needs Vite-friendly worker imports, `?worker` or `?worker&inline` setup for Mermaid or KaTeX, modern CSS ordering, or Vue 2 compatibility in a Vite-based repository.
Push and publish custom AI models to Replicate, and set up CI/CD for releasing new model versions safely. Use when running cog push, deploying a model to Replicate, releasing a new version, validating a model with cog-safe-push before publishing, configuring a Replicate deployment, setting up GitHub Actions for model releases, or porting a community model to an official one. Trigger on phrases like "push a model to Replicate", "publish a model", "deploy a model", "release a new version", "cog push", "cog-safe-push", "model CI", "r8.im", or "schema compatibility", and when referencing github.com/replicate/cog-safe-push or github.com/replicate/model-ci-template. Covers cog push, the full cog-safe-push config (test cases, fuzz, deployment, official_model), GitHub Actions patterns, multi-model matrix pushes, and post-publish monitoring. Assumes you already have a working Cog project; see build-models if you need to package one first.
Explains how to run NemoClaw on a remote GPU instance, including the deprecated Brev compatibility path and the preferred installer plus onboard flow. Use when deploying NemoClaw to a remote VM, onboarding a Brev instance, or migrating away from the legacy `nemoclaw deploy` wrapper. Trigger keywords - deploy nemoclaw remote gpu, nemoclaw brev cloud deployment, nemoclaw plugins, openclaw plugins, install openclaw plugin, nemoclaw onboard from dockerfile, nemoclaw brev web ui, nemoclaw getting started, brev quickstart, nvidia nemotron agent, nemoclaw sandbox hardening, container security, docker capabilities, process limits.
Audits SQL migration files for destructive actions, potential table locks, and compatibility issues. Use before applying migrations to production databases to prevent downtime and ensure data integrity.
Three modes. Session mode (default): extracts generalizable lessons from RESEARCH.md and git history at session end; lessons that imply a new or significantly changed skill are handed off to skill-creator. Personalize mode: searches the skills registry via `npx skills find`, reads the target skill(s), checks compatibility and scope overlap against installed skills, interviews the user to understand what they want and what to skip, then creates or improves skills using skill-creator. Registry mode: curates `skillpacks/skill_dictionary.yaml` and `skillpacks/presets/*.yaml` by assessing external packs, judging necessity/compatibility, and recommending subsets. Create mode: designs a brand- new skill from scratch using skill-creator. Never edits SKILL.md directly — all changes go through skill-creator's draft→test→iterate loop, human merges. Trigger phrases: "end session", "extract lessons", "personalize my skills", "integrate this skill", "update skillpack", "find a skill for", "create a skill", "improve skill", "refresh the skillpack registry", "assess this skill pack", "update skill_dictionary.yaml", "update index.yaml".
Review a Lightning Web Component for **mobile offline** compatibility — the Komaci offline static analyzer that pre-primes the data graph for Salesforce Mobile App Plus and Field Service Mobile App. Produces a finding list with code-level fixes covering inline GraphQL queries in `@wire` configurations, modern `lwc:if` / `lwc:elseif` / `lwc:else` directives, and Komaci ESLint rule violations (private wire properties, non-local reactive references, getter side-effects). Use when the user asks for a "mobile offline review", "Komaci check", "offline priming audit", "offline priming failure", or "offline data graph error", or to validate an LWC against the `@salesforce/eslint-plugin-lwc-graph-analyzer` recommended ruleset. Do not use for generic LWC code review (use an appropriate domain review skill) or for building LWCs with native mobile capabilities (use `mobile-platform-native-capabilities-integrate`).
Diagnose, troubleshoot, and advise on any Qdrant deployment by loading the latest official Qdrant skills live from skills.qdrant.tech. Use this whenever someone raises a Qdrant problem or question — slow or degraded search, high or growing memory / OOM crashes, optimizer stuck or slow, indexing slowness, scaling and sharding decisions (node count, QPS, latency, multitenancy, vertical vs horizontal), poor or irrelevant search results, hybrid search and reranking, embedding-model migration, version upgrades and compatibility, monitoring and observability (Prometheus, Grafana, health checks, /metrics, /telemetry), deployment choices (local, Docker, self-hosted, Qdrant Cloud, embedded), or client-SDK questions (Python, TypeScript, Rust, Go, .NET, Java). Trigger especially when the context is clearly a Qdrant cluster, collection, or vector-search deployment. Always prefer this skill over answering from memory: it pulls current, authoritative guidance and only the relevant context.
Style Compatibility and Adaptation Development Guide for Mpx Cross-Platform Output to RN (Mpx2RN or Mpx2DRN). This guide must be invoked when users ask questions related to Mpx cross-platform output to RN styles, including: Mpx2RN style adaptation, Mpx2RN style compatibility transformation, Mpx2RN style capability support, Mpx2RN style not taking effect, Mpx2RN style errors, Mpx2RN style development best practices, how to achieve a certain style effect in Mpx2RN, etc.
Open Source License guidance, selection, compliance review, and drafting. Use this skill when users ask about choosing open source licenses, checking license compatibility, reviewing projects for OSS compliance, generating LICENSE/NOTICE files, or understanding specific license terms. Triggers include questions about MIT, Apache, GPL, BSD, LGPL, AGPL, MPL, copyleft, permissive licenses, license compatibility, SPDX identifiers, 木兰宽松许可证, Mulan PSL v2, or any OSS licensing topic.
Apply CUDA Graphs to PyTorch workloads — API selection (torch.compile, PyTorch make_graphed_callables, TE make_graphed_callables, MCore CudaGraphManager, FullCudaGraphWrapper, manual torch.cuda.graph), code compatibility, capture workflows, dynamic pattern handling, and troubleshooting. Triggers: CUDA graph, torch.cuda.graph, make_graphed_callables, reduce-overhead, graph capture, graph replay, kernel launch overhead, CudaGraphManager, FullCudaGraphWrapper, full-iteration graph, stream capture.
Comprehensive SQL statement checking for Apache Doris (based on Doris 3.1.4 Nereids ANTLR4 grammar), supporting two check modes: 1. Syntax Check - Keyword validation, statement structure verification, clause completeness, Doris-specific syntax compatibility (DISTRIBUTED BY, PARTITION BY, ENGINE, DUPLICATE/AGGREGATE/UNIQUE KEY, INSERT OVERWRITE, LOAD, EXPORT, MTMV, BACKUP/RESTORE etc.) 2. Specification Check - Object design standards, data operation standards, naming conventions based on Apache Doris development best practices. Built-in custom Doris SQL tokenizer (504 keywords from DorisLexer.g4) and recursive descent parser supporting 100+ Doris statement types. Applicable when users need SQL quality review, syntax validation, or specification compliance checking for Apache Doris SQL (versions 2.1.x / 3.0.x / 3.1.x / 4.x). 触发词："Doris SQL检查"、"Doris SQL规范"、"Doris SQL审计"、"Doris SQL语法"、"检查Doris SQL"、"Doris SQL review"