Python skills

This skill helps you resume interrupted webnovel tasks by precise state tracking and safe recovery options, ensuring seamless progress without guessing.

This skill reviews chapter quality with checker agents and generates structured reports to guide revision.

This skill initializes a deep webnovel project by collecting full story world constraints and generating all pre-writing files for a solid start.

This skill helps you locate implementation and loading points across large codebases by using vexor to perform intent-based file discovery.

This skill converts Markdown into multiple professional formats including DOCX, PDF, HTML, and more, empowering rapid document generation.

This skill converts Markdown into DOCX, HTML, PDF, slides, spreadsheets, and code files, enabling quick multi-format outputs from a single document.

This skill analyzes GitHub pull requests and issues using AI to review changes, answer questions, and provide actionable feedback with sources.

This skill helps you build cross-platform mobile apps with Flutter and React Native, enforcing clean architecture, offline-first design, and platform-specific

This skill eliminates response bloat to save tokens while preserving clarity and essential information in concise outputs.

This skill helps economists run panel data models in Python using pandas and linearmodels with correct fixed effects, clustering, and diagnostics.

This skill helps economists fetch data from FRED, World Bank, and other APIs, returning clean code for reliable macro data pipelines.

This skill helps fetch and summarize dbt documentation by converting URLs to markdown, guiding page searches, and locating relevant topics.

This skill guides you through configuring and troubleshooting the dbt MCP server for Claude, Cursor, and VS Code to enable seamless AI tooling.

This skill answers natural language business questions by querying dbt semantic layer, then explores models or manifests if needed to provide an accurate

This skill guides creating and modifying dbt semantic layer components, including models, entities, dimensions, and metrics, with validation and spec guidance.

This skill evaluates ML research papers following ICML guidelines, providing comprehensive, literature-grounded feedback across claims, methods, experiments,

This skill guides you through tree-based research cycles as an AI co-scientist, ensuring hypothesis-driven, reproducible experiments across domains.

This skill helps you estimate Tinker fine-tuning costs by tokenizing datasets with the correct tokenizer and applying model-specific pricing.

This skill guides ideation and implementation of neuro-symbolic reasoning, combining LLMs with symbolic solvers to design experiments or integrate solvers.

This skill conducts a literature review and crafts a CS research proposal by identifying assumptions, proposing alternatives, and outlining testable validation.

This skill helps you split large uncommitted changes into logical commits by proposing a safe, numbered plan and applying patches precisely.