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Found 1,894 Skills
Evaluate Figma designs from operator persona perspectives through design critique and user experience evaluation. Use when reviewing UX for specific user roles (e.g., air-surveillance-tech, weapons-director), conducting design reviews, or evaluating operator interfaces. Analyzes cognitive load, communication patterns, pain points, and system visibility. Works with Figma MCP (desktop/URL) and Outline docs.
Evaluate and improve user experience of interfaces (CLI, web, mobile)
Evaluate third-party agent skills for security risks before adoption or update. Use when: (1) Installing or updating a skill from skills.sh, ClawHub, or any public registry, (2) Auditing skills for security risks or reviewing PRs that add/update skill dependencies, (3) Building a team/org allowlist of approved skills, (4) Investigating suspicious skill behavior or answering "is this skill safe?" / "should we adopt this skill?"
Use this skill for ANY question about creating test or evaluation datasets for LangChain agents. Covers generating datasets from traces (final_response, single_step, trajectory, RAG types), uploading to LangSmith, and managing evaluation data.
Designs multi-agent system architectures with orchestration patterns, tool schemas, and performance evaluation. Use when building AI agent systems, designing agent workflows, creating tool schemas, or evaluating agent performance.
Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant.
Master dispatcher for all MLflow workflows. Use this skill when the user wants to do anything with MLflow — tracing, evaluating, debugging, or improving an agent. Routes to the right MLflow sub-skill automatically. Triggers on: "use mlflow", "help with mlflow", "mlflow agent", "add mlflow to my project", "trace my agent", "evaluate my agent", or any MLflow task without a specific skill in mind.
Design multi-agent harnesses for long-running autonomous coding tasks. Covers generator/evaluator loops, context reset strategy, sprint contracts, and the planner-generator-evaluator architecture from Anthropic's harness research.
Update financial models with new data — quarterly earnings, management guidance, macro changes, or revised assumptions. Adjusts estimates, recalculates valuation, and flags material changes. Use after earnings, guidance updates, or when assumptions need refreshing. Triggers on "update model", "plug earnings", "refresh estimates", "update numbers for [company]", "new guidance", or "revise estimates".
Spot and evaluate trending product opportunities on Amazon, and tell a real trend from a fad. Reads trend signals, judges where a trend is in its curve, and decides whether a seller can enter in time to profit. Use when a user asks about trending products, hot products, viral products, jumping on a trend, trend spotting, or whether a product is a fad. Trigger phrases: "trending products", "hot products", "viral product", "is this a trend or a fad", "trend spotting", "should I jump on this trend". Works with zero tools.
Research and validate an Amazon product opportunity end to end, and evaluate whether the niche around it is winnable. Assesses demand, competition, profit potential, entry barriers, review wall, differentiation room, and seasonality, and returns a go/no-go with the reasoning. Use when a user asks to research a product, find a product to sell, validate a product idea, assess an opportunity, evaluate a niche, find a profitable niche, judge whether a category is worth entering, or compare niches. Trigger phrases: "product research", "find a product to sell", "validate this product", "is this a good product", "product opportunity", "should I sell this", "niche finder", "evaluate this niche", "is this niche worth it", "good niche", "low competition niche", "should I enter". Works with zero tools. the user describes the product and what they can observe.
Help users develop product taste and intuition. Use when someone wants to improve their product judgment, struggles to evaluate design quality, needs to make decisions without complete data, or wants to build better product instincts.