code-review-preferences
Use when reviewing code, PRs, or discussing code quality standards. Applies team coding standards and review methodology.
domain-expertise-template
Template for creating domain expertise skills. Copy and customize for your specific domain.
standup-formatter
Use when generating standup reports, daily updates, or team status summaries. Formats work activity into concise standup format.
technical-decision-record
Use when making technical decisions, choosing technologies, or documenting architectural choices. Creates ADRs (Architecture Decision Records).
definition.metric_catalog
Document key metrics, definitions, and segmentation required to track product success.
definition.okr_drafting
Draft outcome-oriented OKRs with leading indicators and initiatives tied to the product strategy.
definition.story_map
Generate a structured user story map to visualize workflows, user goals, and release slices.
definition.tech_spike
Scope and prioritize technical spikes that de-risk architecture or implementation questions.
definition.test_strategy
Define the holistic testing approach across functional, non-functional, and automation layers for the initiative.
definition.value_proposition
Shape the value proposition narrative tying customer needs, solution benefits, and proof points together.
delivery.dashboard_brief
Align analysts and designers on the goals, requirements, and storytelling approach for a new or updated dashboard.
delivery.design_review
Facilitate a cross-functional design review capturing decisions, feedback, and implementation guidance.
delivery.release_notes
Generate structured release notes tailored to the specified audience and highlighting value, rollout, and risks.
delivery.roadmap
Create a delivery roadmap that translates strategy into sequenced releases with milestones and dependencies.
delivery.tech_spec
Produce an implementation-ready technical specification with architecture, sequencing, and validation details.
delivery.test_plan
Generate a detailed test plan covering scenarios, environments, data, and reporting for the release.
discovery.data_audit
Inventory available datasets, instrumentation gaps, and data quality considerations for the initiative.
discovery.market_scan
Analyze the competitive and adjacent solution landscape to surface differentiation opportunities.
discovery.problem_framing
Frame the core customer problem, evidence, and success hypothesis before solutioning.
discovery.risk_assessment
Identify potential quality, security, and delivery risks early in discovery to inform mitigation planning.
discovery.tech_landscape
Assess technical patterns, integrations, and constraints in the domain to inform feasibility and strategy.
discovery.user_research
Plan and structure moderated or unmoderated user research sessions that target the given persona and objectives.
optimization.experiment_analysis
Analyze completed experiments and craft executive-ready summaries with insights and recommendations.
optimization.experiment_brief
Prepare an experiment brief outlining hypothesis, design, success metrics, and operational plan.
optimization.metric_review
Conduct a metric review that contextualizes performance trends, flags anomalies, and recommends actions.
optimization.postmortem
Produce a post-incident analysis capturing timeline, root causes, impact, and corrective actions.
optimization.quality_report
Compile a recurring quality report that synthesizes defect trends, automation health, and recommendations.
optimization.retrospective
Facilitate a sprint or release retrospective focusing on insights, actions, and ownership.
pyx
Safe Python code execution using pyx CLI. Use when: running Python, executing scripts, testing code. Triggers: pyx, run python, execute code, test script. Default mode: MANIFEST_IO (file-first with manifest output).
setup-react-app-config
Set up configuratin files for the React project (Biome, Shadcn/UI)
developer-growth-analysis
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, generating a personalized growth report with actionable recommendations.
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
skill-seekers
Generate AI skills (SKILL.md) from documentation websites, GitHub repositories, PDF files, or local codebases using the Skill Seekers CLI. Use when the user wants to create a new AI skill from external documentation, analyze a GitHub repo into a skill, convert a PDF into structured AI knowledge, or package skills for Claude, Gemini, or OpenAI.
alpha-vantage
Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.
csv-data-summarizer
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
edgartools
Python library for accessing, analyzing, and extracting data from SEC EDGAR filings. Use when working with SEC filings, financial statements (income statement, balance sheet, cash flow), XBRL financial data, insider trading (Form 4), institutional holdings (13F), company financials, annual/quarterly reports (10-K, 10-Q), proxy statements (DEF 14A), 8-K current events, company screening by ticker/CIK/industry, multi-period financial analysis, or any SEC regulatory filings.
excel-dcf-modeler
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excel-lbo-modeler
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excel-pivot-wizard
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excel-variance-analyzer
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geopandas
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
hedgefundmonitor
Query the OFR (Office of Financial Research) Hedge Fund Monitor API for hedge fund data including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms. Access time series data on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management. No API key or registration required. Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage or leverage ratios, counterparty concentration, Form PF statistics, repo market data, or OFR financial research data.
invoice-processor
Automatically process invoices (发票) from PDFs/images to Excel spreadsheets using AI vision recognition. Use this skill when users mention "发票", "invoice", "处理发票", "识别发票", "提取发票", or need to convert invoice files to Excel format.
matplotlib
Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.
networkx
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
plotly
Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.
scientific-visualization
Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.
seaborn
Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.
statistical-analysis
Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.
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