Results for “package-analysis”

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Refactoring Analyst

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Builds a compact secret-safe repository pack for AI handoff, review, or large analysis; prefers Repomix when available.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Provides file paths to language-specific reference files for polyglot test analysis skills, enabling framework-aware detection of test markers, assertions, and patterns across .NET, Python, TypeScript, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, and C++.

Analyzes test suites across multiple languages and tags each test with standardized traits (positive, negative, critical-path, etc.) for better test categorization and coverage visibility.

Analyzes .NET project code coverage and CRAP (Change Risk Anti-Patterns) scores to identify risk hotspots, methods blocking coverage gains, and prioritize where to add tests.

Analyzes production code to find gaps in existing tests by reasoning about hypothetical mutations and checking whether tests would catch them.

Generates detailed, technology-agnostic implementation blueprints by analyzing project architecture, technology stacks, and data flow patterns.

Evaluates RAG pipelines using a filesystem-based benchmark with corpus/ and train.json, running evaluate_rag.py to tune retrieval and generation flags and interpret RAGAS metrics.

Cross-repository dependency audit. Scans package manifests for outdated packages, security advisories, version conflicts, and license issues. Produces a prioritized update plan. Supports Node.js, Python, Rust, and Go projects.

Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment. Use when the user wants to assess, evaluate, or review the architecture, design quality, dependency structure, coupling, cohesion, or technical debt of an existing part of the codebase. Not for investigating specific bugs, runtime errors, or failures — use investigate. Not for test planning — use automated-test-planning. Not for file-level code review — use code-review. Not for researching open-ended options, prior art, or how something works — use research. Not for designing a new interface or contract — use design-an-api. Not for writing documentation or architectural decision records.

Analyze suspected malware through static, dynamic, and behavioral techniques, including IOC extraction, YARA or Sigma rules, sandboxing, and anti-analysis behavior detection.

Internal architecture and change-impact review assistant for this repository.

Quickly query genomic reference databases for Ensembl IDs, gene metadata, sequences, BLAST searches, and enrichment analysis using the gget CLI or Python package.

Analyzes codebases to understand existing features, tracing entry points, execution paths, architecture layers, patterns, and dependencies before new development.

Run Bumblebee supply-chain inventory and exposure scans on macOS/Linux to detect compromised packages, extensions, and MCP host configs.

Inspect, profile, clean, reconcile, analyze, visualize, and verify spreadsheet data while preserving formulas, formatting, types, and source files. Use when working with .xlsx, .xlsm, .xls, .ods, .csv, or .tsv files; answering questions from a workbook; auditing formulas or data quality; comparing sheets or versions; producing pivots, charts, forecasts, or summary workbooks; repairing malformed tables; or validating that spreadsheet edits and calculations are accurate.

Analyze which monorepo packages and apps are affected by current changes