Use when writing, reviewing, or refactoring Python to ensure adherence to modern best practices (type syntax, `uv` instead of `python`, linting, formatting, etc.)

Advanced python-docx patterns for handling nested tables, complex cell structures, and content extraction beyond basic .text property. Complements the official docx skill with specialized techniques for forms, checklists, and complex layouts.

Use when creating or editing documents (DOCX, PDF, XLSX, PPTX) that need professional output. Adds visual verification, typography hygiene, and formula patterns.

Build comprehensive, mobile-compatible Obsidian study vaults from academic course materials with checkpoint-based workflow, error pattern recognition, and quality assurance. Battle-tested patterns from 828KB/37-file projects. Works across all subjects - CS, medicine, business, self-study.

Extract PDFs to text and images before reading

Translate DOCX to RTL languages (Arabic, Hebrew, Urdu) preserving exact formatting, tables, colors, layouts. Handles quote normalization and multi-pass matching.

Fill DOCX template forms preserving 100% original structure - logos, footers, styles, metadata. Zero-artifact insertion. Output indistinguishable from manual entry.

Implement RLM-style (Recursive Language Model) orchestration for complex tasks. This skill should be used when facing large context requirements, multi-part tasks that would benefit from parallel execution, or when context rot is a concern. Automatically decomposes tasks, spawns parallel subagents, aggregates results, and iterates until completion. Inspired by the RLM research paper (arXiv:2512.24601).

Connect to local Weaviate vector database and verify connection health

Search and retrieve data from local Weaviate using semantic search, filters, RAG, and hybrid queries

Functional mythological compression for OCTAVE documents. Semantic shorthand for LLM audiences, not prose decoration

Provides the complete content of 'The Swift Programming Language (6.3 beta)' book by Apple. Use this skill when you need to verify Swift syntax, look up language features, understand concurrency, resolve compiler errors, or consult the formal language reference.

Create, view, update, and delete Weaviate collections with schema management (for local Weaviate)

Every AI output has structural blind spots determined by the generation process itself. Future Tokens operations are named, composable instruments that target specific blind spots. They surface new information on every pass because expanding the output changes the blind spot geometry.

Upload and process data into local Weaviate collections with support for single objects, batch uploads, and multi-modal content

Set up and manage a local Weaviate instance using Docker

Validate a Copilot Studio YAML file against the schema and best practices. Use when the user asks to check, validate, or verify a YAML file.

List all available kind discriminator values from the Copilot Studio YAML schema. Use when the user asks what kinds/types are available.

Look up Copilot Studio YAML schema definitions. Use when the user asks about schema structure, element properties, or how to use a specific YAML kind.

Send a message to a published Copilot Studio agent and get its full response. Use when the user asks to test a specific utterance, check how the agent responds, verify a topic was fixed, or do a quick point-test after making YAML changes. Also useful for multi-turn conversation testing.