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Found 1,273 Skills
Create ShinkaEvolve task scaffolds from a target directory and task description, producing `evaluate.py` and `initial.<ext>` (multi-language). Use when asked to set up new ShinkaEvolve tasks, evaluation harnesses, or baseline programs for ShinkaEvolve.
Systematic debugging for ADK agents — trace reading, log analysis, common failure diagnosis, and the debug loop.
Teach AI agents how to query data warehouses accurately using ktx - an executable context layer with skills, memory, and a semantic layer
Use the Data Analysis Agent to perform natural language business analytics, auto-generate SQL queries, create visualizations, and produce business insights from Excel/CSV/databases
Use when working on the Evaluator plugin CLI, jobs, SDK-backed specs, or plugin-owned Evaluator skills.
Find working Deepgram integration examples with third-party platforms and frameworks. Use whenever someone wants to integrate Deepgram with Twilio, LiveKit, LangChain, Vercel AI SDK, Discord, Vonage, Pipecat, Expo, FastAPI, Cloudflare Workers, Slack, Telegram, LlamaIndex, Zoom, Next.js, Nuxt, Django, SvelteKit, NestJS, Spring Boot, CrewAI, Riverside, SignalWire, and more. Examples are full runnable integration demos, not minimal feature snippets.
Model Selection and Recommendation for Alibaba Cloud Tongyi Wanli. Activated when users need to "select, recommend, compare" models, or describe an AI scenario/functional requirement (implying the need to decide which model to use). The core intention is to help users make decisions, not just provide information. Trigger words: recommend model, which one to choose, which is suitable, compare, build a XX, implement XX function, which model is good to use, XX scenario solution. When users involve both model query and model selection at the same time, prioritize using this skill (this skill will read model data internally to complete the recommendation).
Add EAGLE-3 or draft-model speculative decoding to a Jetson vLLM server when TPOT is the bottleneck.
This skill should be used when establishing comprehensive QA testing processes for any software project. Use when creating test strategies, writing test cases following Google Testing Standards, executing test plans, tracking bugs with P0-P4 classification, calculating quality metrics, or generating progress reports. Includes autonomous execution capability via master prompts and complete documentation templates for third-party QA team handoffs. Implements OWASP security testing and achieves 90% coverage targets.
Analyze and improve existing prompts for better performance
Interactive setup wizard for Minitap mobile-use SDK. USE WHEN user wants to set up mobile automation, configure mobile-use SDK, connect iOS or Android devices, or create a new mobile testing project.
Use when evaluating agent performance, building test frameworks, measuring quality, or asking about "agent evaluation", "LLM-as-judge", "agent testing", "quality metrics", "evaluation rubrics", "agent benchmarks"