Practical Python scripts for debugging awf - parse logs, diagnose issues, inspect containers, test domains

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.

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

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.

Behaviour Twin KIT

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

Apple firmware and binary reverse engineering with the ipsw CLI tool. Use when analyzing iOS/macOS binaries, disassembling functions in dyld_shared_cache, dumping Objective-C headers from private frameworks, downloading IPSWs or kernelcaches, extracting entitlements, analyzing Mach-O files, or researching Apple security. Triggers on requests involving Apple RE, iOS internals, kernel analysis, KEXT extraction, or vulnerability research on Apple platforms.

Extract PDFs to text and images before reading

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).

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

QA harness for LLM agents: scenario suites, flake controls, tool sandboxing, LLM-as-judge scoring, and regression protocols.

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

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

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.

Set up and manage a local Weaviate instance using Docker

Connect to local Weaviate vector database and verify connection health

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.

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

Reference for LocalStack AWS service availability by tier (Free/Base/Ultimate). Essential for KECS development to understand which AWS-compatible services can be used locally without cost.

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