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Found 49 Skills
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).
Selects a base model and fine-tuning technique (SFT, DPO, or RLVR) for the user's use case by querying SageMaker Hub. Use when the user asks which model or technique to use, wants to start fine-tuning, or mentions a model name or family (e.g., "Llama", "Mistral") — always activate even for known model names because the exact Hub model ID must be resolved. Queries available models, validates technique compatibility, and confirms selections.
Analyze token usage patterns and recommend cost optimizations with estimated savings
/cs:caio-review <plan> — Eval-demanding Chief AI Officer interrogation of any plan that involves AI: model selection, risk classification, cost economics, or AI hiring.
Execute complex tasks through sequential sub-agent orchestration with intelligent model selection, and LLM-as-a-judge verification
[QwenCloud] Recommend the best Qwen model and parameters. TRIGGER when: choosing between Qwen models, comparing Qwen model pricing, understanding Qwen model capabilities, when an execution skill needs model selection advice, or user explicitly invokes this skill by name (e.g. use qwencloud-model-selector). DO NOT TRIGGER when: non-Qwen model discussions (OpenAI, Gemini, etc.), general AI questions unrelated to Qwen.
Route issue-running automation through a deterministic control plane that selects agent + model from registry, can coordinate multiple safe parallel agents, and executes the unified run-agent runner.
This skill should be used when the user asks to generate an image, create an AI image, produce a product image, generate a visual from a prompt, or check and continue an existing image generation task. Generates images through CreatOK's image generation API and can also recover interrupted generation flows from an existing task id.
Execute complex tasks through sequential sub-agent orchestration with intelligent model selection, meta-judge → LLM-as-a-judge verification
Trigger this skill when building applications with Gemma or for general knowledge inquiries related to Gemma models (e.g. prompt structure, capabilities). Covers model selection, development workflows, and deployment best practices.
Route tasks to optimal agents using learned patterns, model recommendations, and confidence scoring
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification