Data & Analytics

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Pinterest API v5 Development - Authentication, Pins, Boards, Analytics

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Convert AutoCAD DWG files (1983-2026) to Excel databases using DwgExporter CLI. Extract layers, blocks, attributes, and geometry data without Autodesk licenses.

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Use when building Apache Spark applications, distributed data processing pipelines, or optimizing big data workloads. Invoke for DataFrame API, Spark SQL, RDD operations, performance tuning, streaming analytics.

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Build SQL queries for construction databases. Generate optimized SQL queries for construction data retrieval

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Execute use when you need to work with query optimization. This skill provides query performance analysis with comprehensive guidance and automation. Trigger with phrases like "optimize queries", "analyze performance", or "improve query speed".

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Use when optimizing SQL queries, designing database schemas, or tuning database performance. Invoke for complex queries, window functions, CTEs, indexing strategies, query plan analysis.

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Analyze detected vulnerabilities to assess realistic exploitability by examining control flow, input sources, sanitization logic, and execution context. Use when users need to: (1) Determine if a vulnerability is actually exploitable in practice, (2) Assess severity and impact of security issues, (3) Prioritize vulnerability remediation, (4) Understand attack vectors and exploitation conditions, (5) Generate exploitability reports with proof-of-concept scenarios. Focuses on injection vulnerabilities (SQL, command, XSS, path traversal, LDAP) with detailed analysis of reachability, controllability, sanitization, and impact.

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Track and analyze OpenRouter usage patterns. Use when optimizing costs or understanding usage. Trigger with phrases like 'openrouter analytics', 'openrouter usage', 'openrouter metrics', 'track openrouter'.

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Queries data warehouse and answers business questions about data. Handles questions requiring database/warehouse queries including "who uses X", "how many Y", "show me Z", "find customers", "what is the count", data lookups, metrics, trends, or SQL analysis.

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Convert DGN files (v7-v8) to Excel databases. Extract elements, levels, and properties from infrastructure CAD files.

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Convert IFC files (2x3, 4x1, 4x3) to Excel databases using IfcExporter CLI. Extract BIM data, properties, and geometry without proprietary software.

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Statically analyze code to detect security vulnerabilities including buffer overflows, injection risks (SQL, command, XSS), insecure deserialization, improper authentication, hard-coded credentials, and unsafe cryptography. Use when: (1) Performing security code review, (2) Analyzing code for OWASP Top 10 vulnerabilities, (3) Identifying CWE-classified weaknesses, (4) Generating security audit reports, (5) Reviewing code before deployment, or (6) Assessing third-party code security. Findings categorized by CWE ID and severity (Critical/High/Medium/Low).

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Load and parse DDC CWICR construction cost database from multiple formats: Parquet, Excel, CSV, Qdrant snapshots. Foundation for all CWICR operations.

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Weighted pandas DataFrames for survey microdata analysis - inequality, poverty, and distributional calculations

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Convert construction data to/from Parquet format. Optimize storage, enable fast queries, and integrate with data lakehouses.

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Forecast project outcomes using historical data: cost overruns, schedule delays, risk probabilities. Machine learning models for construction prediction.

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Analyze construction labor productivity using data analytics. Track worker performance, identify inefficiencies, predict resource needs, and optimize crew allocation for maximum efficiency.

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Identifies third-party services including payments, analytics, auth, CRM, and support

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When the user wants to analyze website traffic sources, attribution, or dark traffic. Also use when the user mentions "traffic sources," "dark traffic," "direct traffic," "UTM parameters," "traffic attribution," or "channel analysis."

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Extract and analyze data from construction ERP systems. Pull project data for analytics, reporting, and integration.

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Handle CSV files from construction software exports. Auto-detect delimiters, encodings, and clean messy data.

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Automate construction data processing using LLM (ChatGPT, Claude, LLaMA). Generate Python/Pandas scripts, extract data from documents, and create automated pipelines without deep programming knowledge.

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Automatically generate Excel reports from data sources including CSV, databases, or Python data structures. Supports data analysis reports, business reports, data export, and template-based report generation using pandas and openpyxl. Activate when users mention Excel, spreadsheet, report generation, data export, or business reporting.

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Use when querying, modifying, or converting JSON, YAML, TOML, XML, CSV, HCL, or INI with dasel v3. Complete reference for selectors, functions, conditionals, variables, spread operator, type casting, and format-specific patterns.

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Extract structured data from construction PDFs. Convert specifications, BOMs, schedules, and reports from PDF to Excel/CSV/JSON. Use OCR for scanned documents and pdfplumber for native PDFs.

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Analyze budget vs actual variances in Excel with drill-down and root cause analysis. Use when performing variance analysis or explaining budget differences. Trigger with phrases like 'excel variance', 'analyze budget variance', 'actual vs budget'.

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Comprehensive Pandas toolkit for construction data analysis. Filter, group, aggregate BIM elements, calculate quantities, merge datasets, and generate reports from structured construction data.

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Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership questions.

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Toolkit for comprehensive Spreadsheet reading, creation, editing, and analysis with visual quality control. Use to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing tabular data, (3) Modifying existing spreadsheets while preserving formulas, (4) Building financial models with proper formatting, (5) Data visualization with in-sheet charts, or any other spreadsheet tasks.

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Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualisation. Use when working with spreadsheets (.xlsx, .xlsm, .csv, .tsv) for creating new spreadsheets with formulas and formatting, reading or analysing data, modifying existing spreadsheets while preserving formulas, data analysis and visualisation, or recalculating formulas.

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Load gene expression count matrices from various formats including CSV, TSV, featureCounts, Salmon, kallisto, and 10X. Use when importing quantification results for downstream analysis.

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Create, edit, and analyze office documents (PDF, DOCX, PPTX, XLSX). Use when working with PDFs, Word documents, PowerPoint presentations, or Excel spreadsheets. Covers text extraction, form filling, document creation, and data analysis.

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Generate pivot tables and charts from raw data using natural language - analyze sales by region, summarize data by category, and create visualizations effortlessly Activates when you request "excel pivot wizard" functionality.

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Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified. Originally from OpenAI's curated skills catalog.

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This skill provides guidance for analyzing log files across date ranges and producing summary statistics. Use when tasks involve parsing log files, counting log entries by severity (ERROR, WARNING, INFO), aggregating by date ranges (today, last N days, month-to-date), or producing CSV reports from log data.

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Guidance for SQL query optimization tasks. This skill should be used when optimizing slow SQL queries, improving database performance, or rewriting queries to be more efficient. Covers query plan analysis, benchmarking strategies, and database-specific optimization techniques.