Data Science

Map design trade-offs across dimensions when choosing between approaches. Use when: (1) asked to compare approaches, identify trade-offs, weigh pros and cons, or clarify what would be sacrificed by a choice, (2) recommending an approach based on a single criterion without acknowledging what it sacrifices, (3) presenting multiple options but only listing features rather than explaining what each optimizes for and costs, (4) deep in implementation details before establishing what qualities actually matter for the decision, (5) a solution reveals significant downsides that trade-off analysis should have predicted, (6) treating design choices as objectively right or wrong rather than as positions in a trade-space

Threat modeling methodologies using STRIDE, attack trees, and risk assessment for proactive security analysis. Use when designing secure systems, conducting security reviews, or identifying potential attack vectors in applications.

Copilot agent that assists with performance analysis, bottleneck detection, optimization strategies, and benchmarkingTrigger terms: performance optimization, performance tuning, profiling, benchmark, bottleneck analysis, scalability, latency optimization, memory optimization, query optimizationUse when: User requests involve performance optimizer tasks.

Analyze coordination patterns, handoff mechanisms, and state sharing in multi-agent systems. Use when (1) understanding how agents transfer control, (2) evaluating shared vs isolated state patterns, (3) mapping communication protocols between agents, (4) assessing multi-agent orchestration approaches, or (5) comparing coordination models across frameworks.

Coordinate multi-tool workflows with guardrails; use when asked to chain retrieval, analysis, and action steps.

Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms

Develop implicit pattern recognition into explicit understanding. Use when analysis identifies something without fully explaining why, when solutions meet requirements but coherence issues remain unarticulated, or when a thread seems promising but the reasoning hasn't been formalized.

Systematic analysis and refinement of specifications, requirements, architecture designs, and project plans. Use when the user wants to identify gaps, weaknesses, inefficiencies, or complications in a proposed plan, specification, or design document. Triggers on gap analysis, specification review, requirements analysis, architecture critique, design validation, plan assessment, weakness identification, assumption auditing, or when users share specs/plans asking for feedback. Produces actionable findings with remediations and maintains analysis state across iterations.

Expert at automatically applying improvements to Claude Code components based on quality analysis. Enhances descriptions, optimizes tool permissions, strengthens security, and improves usability. Works in conjunction with analyzing-component-quality skill.

Enterprise code quality orchestrator with TRUST 5 validation, proactive analysis, and automated best practices enforcement

Assess credit risk and default probability for bonds using credit spreads, rating transitions, and recovery analysis. Requires numpy>=1.24.0, pandas>=2.0.0, scipy>=1.10.0. Use when evaluating corporate bonds, analyzing credit events, estimating default probabilities, or managing credit portfolio risk.

A simple test skill that analyzes code files and provides a summary report. Use when asked to analyze code structure, count files, or provide project statistics. Demonstrates Claude Code skill functionality.

Systematic gap analysis for claimed vs actual work completion. Uses 100+ sequential thoughtsto identify assumptions, partial completions, missing components, and rationalization patterns.Validates completion claims against original plans, detects scope deviations, reveals quality gaps.Essential for self-assessment before declaring work complete. Use when: claiming completion,final reviews, quality audits, detecting rationalization patterns in own work.

Practical application guide for HUMMBL's 6 transformations (Perspective, Inversion, Composition, Decomposition, Recursion, Meta-Systems). Includes when to use each transformation, combination patterns, analysis templates, output formats, real-world examples, and common pitfalls. Essential for applying mental models effectively in problem-solving and analysis.

Complete MXQL (Metrics Query Language) toolkit for generating, analyzing, validating, and testing queries. Supports conversational query generation, automated validation, comprehensive analysis with optimization suggestions, and test query generation with sample data. Use this for all MXQL-related tasks including creating queries, debugging, optimization, and testing.

Analyze percentile metrics (tdigest type) using OPAL for latency analysis and SLO tracking. Use when calculating p50, p95, p99 from pre-aggregated duration or latency metrics. Covers the critical double-combine pattern with align + m_tdigest() + tdigest_combine + aggregate. For simple metrics (counts, averages), see aggregating-gauge-metrics skill.

Use when user says "update story tree", "show story tree", "show me a map", "story map", "tree diagram", "show stories", "view stories", "list stories", or asks for story visualization or tree status - autonomously maintains hierarchical story backlog by analyzing git commits, identifying under-capacity nodes, and coordinating story generation to fill gaps. Works with SQLite database using closure table pattern, prioritizes shallower nodes first, and tracks implementation status through commit analysis.

Financial data collection and visualization using TradingView lightweight-charts.Fetches market data from trusted sources and renders interactive charts.USE WHEN user says "create chart", "visualize stock data", "show price chart","fetch market data", "display financial chart", "chart [ticker]", "plot [asset]",or any request related to financial data visualization and charting.

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

Analytics and data analysis workflow skill