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Found 1,288 Skills
Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.
Improve visibility in AI search and answer engines (ChatGPT, Perplexity, Gemini, Google AI Overviews) using GEO: crawl controls (robots/WAF/llms.txt), answer-ready content and entity pages, citation strategy, and measurement (query bank, share of model).
Use when the user needs human-in-the-loop workflows in Airflow (approval/reject, form input, or human-driven branching). Covers ApprovalOperator, HITLOperator, HITLBranchOperator, HITLEntryOperator. Requires Airflow 3.1+. Does not cover AI/LLM calls (see airflow-ai).
Guides users through distributing Tauri applications to the iOS App Store, including Apple Developer enrollment, Xcode configuration, provisioning profiles, code signing, TestFlight beta testing, and App Store submission processes.
Structured observability with Pydantic Logfire and OpenTelemetry. Use when: (1) Adding traces/logs to Python APIs, (2) Instrumenting FastAPI, HTTPX, SQLAlchemy, or LLMs, (3) Setting up service metadata, (4) Configuring sampling or scrubbing sensitive data, (5) Testing observability code.
Production-ready skill for integrating TheSys C1 Generative UI API into React applications. This skill should be used when building AI-powered interfaces that stream interactive components (forms, charts, tables) instead of plain text responses. Covers complete integration patterns for Vite+React, Next.js, and Cloudflare Workers with OpenAI, Anthropic Claude, and Cloudflare Workers AI. Includes tool calling with Zod schemas, theming, thread management, and production deployment. Prevents 12+ common integration errors and provides working templates for chat interfaces, data visualization, and dynamic forms. Use this skill when implementing conversational UIs, AI assistants, search interfaces, or any application requiring real-time generative user interfaces with streaming LLM responses. Keywords: TheSys C1, TheSys Generative UI, @thesysai/genui-sdk, generative UI, AI UI, streaming UI components, interactive components, AI forms, AI charts, AI tables, conversational UI, AI assistants UI, React generative UI, Vite generative UI, Next.js generative UI, Cloudflare Workers generative UI, OpenAI generative UI, Claude generative UI, Anthropic UI, Cloudflare Workers AI UI, tool calling UI, Zod schemas UI, thread management, theming UI, chat interface, data visualization, dynamic forms, streaming LLM UI
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, constructing context from retrieved documents, adding citations, or implementing hybrid search.
Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) strategies for AI-powered search visibility in ChatGPT, Perplexity, Google AI Overviews, and other AI search platforms. Use when working with aeo, geo, ai search, chatgpt search, perplexity, ai overviews, generative search, llm visibility.
Async communication patterns using message brokers and task queues. Use when building event-driven systems, background job processing, or service decoupling. Covers Kafka (event streaming), RabbitMQ (complex routing), NATS (cloud-native), Redis Streams, Celery (Python), BullMQ (TypeScript), Temporal (workflows), and event sourcing patterns.
Use this when the user explicitly requests to "verify/optimize in-text citations of the `{topic}_review.tex` review" or to "run check-review-alignment". Use the host AI's semantic understanding to verify each citation against the literature content one by one. **Only when fatal citation errors are found**, make minimal rewrites to the "sentences containing citations", and reuse the rendering script of `systematic-literature-review` to output PDF/Word (the script does not directly call the LLM API locally). Core principle: **Do not modify for the sake of modifying**. When it is uncertain whether it is a fatal error, keep the original content and issue a warning in the report. ⚠️ Not applicable in the following cases: - The user only wants to generate the main body of a systematic review (should use systematic-literature-review) - The user only wants to add/verify BibTeX entries (should use a dedicated bib management process)
AD Certificate Services attack playbook. Use when targeting misconfigured AD CS for privilege escalation via ESC1-ESC13 template abuse, NTLM relay to enrollment, CA officer abuse, and certificate-based persistence.
Grafana Cloud Application Observability (APM), Frontend Observability (RUM/Faro), and AI Observability. Covers RED metrics (Rate/Error/Duration), service maps, span metrics from traces, Faro JavaScript/React SDK for browser instrumentation, session replay, AI/LLM model monitoring, and integration with traces/logs/profiles for full-stack correlation. Use when setting up APM, configuring frontend monitoring, analyzing service performance, or monitoring AI/LLM applications.