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Found 1,943 Skills
Use when comparing multiple named alternatives across several criteria, need transparent trade-off analysis, making group decisions requiring alignment, choosing between vendors/tools/strategies, stakeholders need to see decision rationale, balancing competing priorities (cost vs quality vs speed), user mentions "which option should we choose", "compare alternatives", "evaluate vendors", "trade-offs", or when decision needs to be defensible and data-driven.
Product interaction and UX expert. Use when reviewing UI/UX, conducting heuristic evaluations, designing user journeys, applying cognitive psychology principles, or ensuring WCAG 2.2 accessibility compliance.
Paper reviewer that evaluates machine learning research projects following official ICML reviewer guidelines. Provides comprehensive reviews with actionable feedback across all key dimensions: claims/evidence, relation to prior work, originality, significance, clarity, and reproducibility. Also provides formative feedback on incomplete drafts, proposals, and research code repositories. MANDATORY TRIGGERS: review paper, ICML review, paper review, evaluate paper, research paper feedback, ML paper review, conference review, academic review, paper critique, NeurIPS review, ICLR review, project proposal, research proposal, paper draft, early feedback, incomplete paper, work in progress, WIP review, review repo, review codebase, research project review
Master Alex Hormozi's offer creation framework from "$100M Offers" (2021). Build irresistible offers using the Value Equation, stacking, guarantees, and scarcity. Use when: Creating new product or service offers; Restructuring existing offers for higher conversions; Pricing premium products and services; Building offer stacks with bonuses and guarantees; Choosing target markets for maximum leverage
This skill should be used when the user asks to review, proofread, check, or evaluate content. It provides comprehensive text review (grammar, logic, compliance) and version evaluation (A/B testing, comparison analysis). Text review automatically adds AI disclaimer at the end.
Build and run LLM-as-judge evaluation pipelines using Amazon Bedrock Evaluation Jobs with pre-computed inference datasets. Use when setting up automated model evaluation, designing test scenarios, collecting pre-computed responses, configuring custom metrics, creating AWS infrastructure, running evaluation jobs, parsing results, and iterating on findings.
Analyzes events through economic lens using supply/demand, incentive structures, market dynamics, and multiple schools of economic thought (Classical, Keynesian, Austrian, Behavioral). Provides insights on market impacts, resource allocation, policy implications, and distributional effects. Use when: Economic events, policy changes, market shifts, financial crises, regulatory decisions. Evaluates: Incentives, efficiency, opportunity costs, market failures, systemic risks.
Score assistant responses for guidance & actionability on a strict 1-5 scale, then return strict JSON only with dimension, score, rationale, and improvement suggestions. Use when the user asks to evaluate how actionable, helpful, or step-by-step a response is.
Execute tasks through systematic exploration, pruning, and expansion using Tree of Thoughts methodology with multi-agent evaluation
Turn rough ideas into structured, validated idea documents through collaborative dialogue. Explores context, asks clarifying questions one at a time, proposes alternative approaches with feasibility evaluation, and produces documents ready for requirements definition. Use when: "ideation", "brainstorm", "new idea", "explore an idea", "I want to build", "what if we", "let's think about", "propose approaches", "evaluate this idea", "idea document", "アイデア出し", "案出し", "ブレスト", "アイデアを整理", "検討したい".
This skill is used when users explicitly request "review NSFC proposals", "simulate expert review", or "evaluate NSFC applications". It simulates the perspective of domain experts to conduct multi-dimensional reviews of NSFC proposals, outputting graded issues and actionable modification suggestions. ⚠️ Not applicable: when users only want to write/modify a specific section of a proposal (use the nsfc-*-writer series skills instead), only want to understand review criteria (answer directly), or have no clear "review/evaluate" intent.
Teaches learners to extract transferable design lessons from real-world codebases through critical evaluation and systematic exploration. Use when a learner wants to study existing code to learn patterns, architecture, or design decisions—not just understand what it does. Guides through navigation, pattern recognition, critical evaluation (deliberate choice vs. compromise), and lesson extraction. Triggers on phrases like "learn from this codebase", "study how X is implemented", "understand design patterns in Y", or when a learner wants to improve by reading real code.