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Access Salesforce CRM to view accounts, contacts, leads, opportunities, and custom objects. Use when user mentions Salesforce, CRM, accounts, contacts, leads, opportunities, or sales data. Uses Python simple-salesforce library for reliable access.
Python library for programmatic PDF generation and creation. Use when user wants to generate PDFs from scratch, create invoices, reports, certificates, labels, or custom documents with precise control over layout, fonts, graphics, tables, and charts. Supports both low-level drawing (Canvas) and high-level documents (Platypus).
Use this skill when you need to add a new Python indicator to AERA.
Comprehensive analysis framework for Fixed Indexed Annuities (FIAs). Use when analyzing, comparing, or evaluating FIA products including surrender charges, index options, crediting methods, riders, commissions, and suitability. Creates detailed product profiles with 40-question suitability assessments and LLM-friendly scoring methodology. Use for internal product analysis, client suitability determination, or when building product comparison documents.
Analyze datasets using Python with pandas, numpy, and visualization libraries. Generates statistical summaries, identifies patterns, creates charts, and provides insights. Use when analyzing CSV/Excel files, exploring data, creating visualizations, or when users mention data analysis, statistics, charts, or datasets.
This skill should be used when users request comprehensive analysis of technology ecosystems, comparing multiple libraries/frameworks/tools with quantitative metrics from GitHub and web research. Trigger words include "ecosystem analysis", "compare libraries", "analyze React/Vue/Python ecosystem", "trending libraries", "technology stack comparison", or requests to evaluate multiple technical tools with data-driven insights.
Generate, refactor, and maintain Python live trading bots for NQ futures prop firm trading (Apex Trader Funding). Supports Databento API for market data, TradersPost for execution, eval/PA modes, custom strategies, and comprehensive production features. Triggers: "live trading bot", "Python bot", "NQ bot", "futures bot", "create bot", "refactor bot", "/bot:new", "/bot:refactor", "/bot:custom".
Use when working in mm-ibkr-gateway to access market data, account summary, positions, PnL, or orders directly in Python via ibkr_core. Covers connecting with IBKRClient, using market/account/order helpers, and safety rules for preview, place, cancel, and status.
Expert in quantitative finance, algorithmic trading, and financial data analysis using Python (Pandas/NumPy), statistical modeling, and machine learning.
Analyze web measurement data with Python/pandas/SQL. Use when user mentions 'analyze data', 'traffic analysis', 'statistics', 'pandas', 'SQL query', or 'plot results'.
Provides guidance and explanations on Python code structure, organization, and architectural patterns tailored for students and beginners.
Performance profiling best practices using py-spy and other Python profiling tools. Activated when profiling code, analyzing bottlenecks, or optimizing performance.
Systems-level performance engineering for Rust, C/C++, and Python codebases. Use when profiling, debugging performance bottlenecks, analyzing CPU/memory usage, finding slow code paths, optimizing hot loops, investigating cache misses, analyzing compile times, or improving runtime performance. Triggers on queries about flamegraphs, perf, valgrind, profilers, benchmarking, or "why is this slow".
Generate initial project planning documents (PVS, ADR, Tech Spec, Roadmap) from a project concept description. Use when starting a new project, when docs/planning/ contains placeholder files, or when user requests project planning document generation.
Search and retrieve Bluetooth SIG Qualified Products data. Use when users need to look up Bluetooth certified products, search by company name/product name/model number, or retrieve qualification details from the Bluetooth SIG database. Provides Python client, request/response handling, and data extraction guidance.
Modern Python coaching covering language foundations through advanced production patterns. Use when asked to "write Python code", "explain Python concepts", "set up a Python project", "configure Poetry or PDM", "write pytest tests", "create a FastAPI endpoint", "run uvicorn server", "configure alembic migrations", "set up logging", "process data with pandas", or "debug Python errors". Triggers on "Python best practices", "type hints", "async Python", "packaging", "virtual environments", "Pydantic validation", "dependency injection", "SQLAlchemy models".
This skill provides comprehensive backend REST API integration for Asleep sleep tracking platform. Use this skill when building server-side applications, API proxies for mobile apps, webhook event handlers, cross-platform backends (React Native, Flutter), analytics dashboards, or multi-tenant sleep tracking systems. Covers authentication, user management, session retrieval, statistics, webhook integration, and production-ready patterns with code examples in Python, Node.js, and curl.
MCP-free Todoist integration with GTD coaching. Uses Python CLI (todoist) to query Todoist API v1 directly. Provides semantic understanding of the user's GTD structure (outcomes as sections, team vs personal, 3-tier ontology), query patterns, and outcome quality coaching. Also handles weekly review orchestration and pattern detection. Triggers on 'clean up outcomes', 'team priorities', 'Q4 review', 'is this a good outcome', 'weekly review', 'am I overcommitting', 'check my patterns', 'should I take this on', 'I said yes to', 'another meeting', 'they asked me to', 'scope creep', 'this grew into', 'freedom score', or ANY Todoist-related task. (user)
MCP-free Todoist integration with GTD coaching. Uses Python CLI (scripts/todoist.py) to query Todoist API v1 directly. Provides semantic understanding of the user's GTD structure (outcomes as sections, team vs personal, 3-tier ontology), query patterns, and outcome quality coaching. Also handles weekly review orchestration and pattern detection. Triggers on 'clean up outcomes', 'team priorities', 'Q4 review', 'is this a good outcome', 'weekly review', 'am I overcommitting', 'check my patterns', 'should I take this on', 'I said yes to', 'another meeting', 'they asked me to', 'scope creep', 'this grew into', 'freedom score', or ANY Todoist-related task. (user)
