What does quant-analysis do?
Quantitative analysis methodology - a 5-stage bottom-up framework applicable to any dataset. Works as a Claude skill and standalone script, with a sedimentation mechanism for self-evolving methodology.
Quantitative analysis methodology - a 5-stage bottom-up framework applicable to any dataset. Works as a Claude skill and standalone script, with a sedimentation mechanism for self-evolving methodology.
This skill provides a structured quantitative analysis methodology based on a 5-stage bottom-up framework. It is designed to work with any dataset, making it highly versatile. The skill supports both Claude AI integration and standalone script execution, allowing for flexible usage. A key feature is its 'sedimentation' mechanism, which enables the methodology to continuously self-evolve and improve over time by learning from previous analyses. This is particularly useful for developers and data analysts who need a systematic, repeatable approach to quantitative analysis that can adapt and refine itself without manual intervention.
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Quantitative analysis methodology - a 5-stage bottom-up framework applicable to any dataset. Works as a Claude skill and standalone script, with a sedimentation mechanism for self-evolving methodology.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.