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Found 344 Skills
Execute tasks through systematic exploration, pruning, and expansion using Tree of Thoughts methodology with multi-agent evaluation
MUST READ before running any ADK evaluation. ADK evaluation methodology — eval metrics, evalset schema, LLM-as-judge, tool trajectory scoring, and common failure causes. Use when evaluating agent quality, running adk eval, or debugging eval results. Do NOT use for API code patterns (use adk-cheatsheet), deployment (use adk-deploy-guide), or project scaffolding (use adk-scaffold).
Codified expertise for quality control, non-conformance investigation, root cause analysis, corrective action, and supplier quality management in regulated manufacturing. Informed by quality engineers with 15+ years experience across FDA, IATF 16949, and AS9100 environments. Includes NCR lifecycle management, CAPA systems, SPC interpretation, and audit methodology. Use when investigating non-conformances, performing root cause analysis, managing CAPAs, interpreting SPC data, or handling supplier quality issues.
Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
Transform vague prompts into precise, well-structured specifications using EARS (Easy Approach to Requirements Syntax) methodology. This skill should be used when users provide loose requirements, ambiguous feature descriptions, or need to enhance prompts for AI-generated code, products, or documents. Triggers include requests to "optimize my prompt", "improve this requirement", "make this more specific", or when raw requirements lack detail and structure.
LLM-as-judge methodology for comparing code implementations across repositories. Scores implementations on functionality, security, test quality, overengineering, and dead code using weighted rubrics. Used by /beagle:llm-judge command.
Screen and identify undervalued stocks with strong fundamentals using professional equity research methodology. Use when the user asks to find undervalued stocks, screen for cheap or bargain stocks, identify value investing opportunities, perform fundamental stock analysis, find stocks trading below intrinsic value, or requests a stock screener based on financial metrics like P/E ratio, debt-to-equity, free cash flow, or ROIC.
Create Product Requirements Documents (PRD) following SDD methodology - Layer 2 artifact defining product features and user needs
Perl testing patterns using Test2::V0, Test::More, prove runner, mocking, coverage with Devel::Cover, and TDD methodology.
Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices.
Guides LLM agents through large-scale coding tasks using a spec-driven, phase-by-phase methodology covering requirement definition, planning, algorithm design, and implementation with OOP principles and language-specific coding standards. Use when starting a new software project, implementing a complex feature, refactoring existing code, or when you need a disciplined step-by-step approach to any non-trivial coding task.
Philip Tetlock's Superforecasting framework applied to a business decision, investment thesis, or strategic question. Spawns a team of specialist agents — Calibrator, Decomposer, Updater, Devil's Advocate, Scorekeeper — who each apply a different piece of the superforecasting methodology. The lead synthesizes into a calibrated probability estimate with Brier-scoreable predictions, explicit base rates, and an accountability structure for keeping score over time. Use when the user says "tetlock this", "what's the probability", "how confident should I be", "forecast this", "calibrate this", proposes a business thesis and wants probabilistic stress-testing, or wants to apply superforecasting to a decision. Works standalone or after /munger.