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Found 1,767 Skills
Expert in enterprise training system design and curriculum development — proficient in training needs analysis, instructional design methodology, blended learning program design, internal trainer development, leadership programs, and training effectiveness evaluation and continuous optimization.
Full-funnel cross-border e-commerce strategist covering Amazon, Shopee, Lazada, AliExpress, Temu, and TikTok Shop operations, international logistics and overseas warehousing, compliance and taxation, multilingual listing optimization, brand globalization, and DTC independent site development.
Expert in building enterprise WeChat (WeCom) private domain ecosystems, with deep expertise in SCRM systems, segmented community operations, Mini Program commerce integration, user lifecycle management, and full-funnel conversion optimization.
Run conversion rate optimization through hypothesis-driven testing including audit, hypothesis generation, test design, statistical analysis, and rollout decisions. Use this skill whenever the user wants to optimize conversion, run A/B tests, audit a funnel, generate test hypotheses, design experiments, or analyze test results. Triggers on conversion optimization, CRO, A/B test, split test, multivariate test, hypothesis, conversion funnel, funnel audit, experiment design, statistical significance, lift, optimization. Also triggers when the user has a conversion problem and isn't sure where to start, or when test results are ambiguous and need interpretation.
Package and build custom AI models with Cog for deployment on Replicate. Use when creating a cog.yaml or predict.py, defining model inputs and outputs, loading model weights at setup time, building Docker images for ML models, serving locally with cog serve or cog predict, or porting a HuggingFace, GitHub, or ComfyUI model to run on Replicate. Trigger on phrases like "build a model", "package a model", "create a Cog model", "wrap a model", "containerize an AI model", "predict.py", "cog.yaml", "BasePredictor", or "Cog container", and when referencing cog.run, github.com/replicate/cog, or github.com/replicate/cog-examples. Covers GPU and CUDA setup, pget for fast weight downloads, async predictors with continuous batching, streaming outputs, and cold-boot optimization for image, video, audio, and LLM models. For pushing built models to Replicate, see publish-models. For running existing models, see run-models.
Generate a /goal mega prompt for Claude Code or Codex CLI by interviewing the user about their task. Use when the user wants to define a long-horizon autonomous goal — migration, refactor, feature build, optimization loop, test fixing, research project, learning system, or any task where the agent should run end-to-end without hand-holding. Trigger on: "help me write a goal", "I want Claude to keep working until...", "run this autonomously", "set a /goal", or any request that implies sustained agentic execution toward a non-trivial outcome. The skill conducts a structured interview (one question at a time) to extract outcome, context, success criteria, constraints, and quality bar — then outputs a filled-in mega prompt ready to paste into Claude Code or Codex.
Track, optimize, and control token consumption across multi-agent systems. Covers budget allocation, real-time monitoring, cost attribution, per-agent limits, and proactive cost optimization for production LLM deployments.
Product listing optimization — titles, descriptions, images, video, attributes for TikTok search
Design, test, and optimize prompts for LLM interactions. Cover prompt patterns (few-shot, chain-of-thought, ReAct), system prompt design, output formatting, prompt evaluation, and prompt optimization techniques. Triggers on "write prompt", "optimize prompt", "design system prompt", "few-shot examples", "chain of thought", "prompt evaluation", "LLM output formatting", "prompt testing", or "prompt patterns".
Use when an SGLang, vLLM, or TensorRT-LLM serving/model optimization task needs prior model-family PR evidence. Query and read the PR-driven history docs under model-pr-optimization-history before choosing source paths, fast paths, kernel/fusion ideas, regression risks, or validation lanes.
Alibaba Cloud PolarDB-X Distributed Database AI Assistant. Use for PolarDB-X cluster management, topology inspection, performance diagnostics, SQL optimization, data distribution analysis, elastic scaling diagnostics, connection/session analysis, security audit, backup/restore, parameter tuning, and other O&M operations. Triggers: "PolarDB-X", "distributed database", "pxc-", "DN/CN nodes", "data sharding", "PolarDB-X diagnostics", "PolarDB-X performance", "PolarDB-X slow SQL", "YaoChi Agent", "PolarDB-X topology", "PolarDB-X backup", "PolarDB-X security audit", "PolarDB-X scaling"
Cloudflare Workers performance optimization with CPU, memory, caching, bundle size. Use for slow workers, high latency, cold starts, or encountering CPU limits, memory issues, timeout errors.