Skill UI

A comprehensive guide for creating and maintaining an atomic, index-driven knowledge base (KB) using Markdown. This method enables AI agents to bypass traditional vector search limitations by reading a central index file (INDEX.md) and opening only the most relevant, highly signaled notes, drastically improving context efficiency.

This skill analyzes local Q&A session JSONL files to produce a complete, auditable weekly report in Markdown format. It supports generating routine weekly summaries, comparing performance across consecutive time windows, and identifying key trends and risks. The output is a single, self-contained Markdown file designed to provide sufficient aggregates and structure for downstream documentation rendering (e.g., Feishu or whiteboards), without needing external data sources or APIs.

This skill provides a comprehensive framework for conducting GDPR Chapter V Transfer Impact Assessments (TIA). It adheres to EDPB guidelines and CNIL recommendations, guiding users through the 6-step methodology. It assesses transfer qualification, adequacy mechanisms (Art. 45), and full risk assessments (Art. 46), while generating standardized reports in Markdown, DOCX, and JSON formats. Ideal for compliance officers managing international data flows.

Knap is a command-line tool that renders Markdown templates using structured data like JSON or CSV. It supports variables, filters, and logic to batch-generate notes, format Defuddle output, and validate templates. Ideal for developers automating note creation and content processing workflows.

Generate reproducible DRAFT master agreements from one Markdown template plus a per-counterparty JSON spec, with role-selected clauses, rendered Schedule A tables and signature blocks. Suited to NDAs, referral, sourcing and master services papering at scale.

Condenses scholarly legal articles by moving nonessential detail from the body into substantive footnotes while preserving every word and keeping the argument self-sufficient. Handles Markdown and Word (.docx), integrates moved material with existing notes, measures a user-specified relegation fraction (25% by default), and delivers a move-by-move memo. Use when asked to push detail into footnotes, relegate to footnotes, footnote the caveats, move the digressions down, or tighten a dense draft without deleting content.

Audit and fix a site's readiness for AI browsing agents: the Lighthouse Agentic Browsing fraction, accessibility tree, robots.txt and Content-Signal, WAF treatment of agent traffic, llms.txt, Markdown delivery, ai-catalog.json, /.well-known files and WebMCP tools.

Convert text, markdown, or summaries into listenable MP3 audio using local CPU-only neural TTS. Rewrites prose for the ear, synthesizes with pocket-tts, and supports chaining with other skills for spoken briefings.

Transform audio and video recordings into professional Markdown documentation with intelligent summaries. Supports batch processing, speaker diarization, and subtitle generation for formats like MP3, WAV, M4A, and more. Ideal for meeting minutes, interviews, lectures, and content creation.

Interactively interviews the user to extract project vision, preferences, and decisions, then generates or updates README and Architecture Decision Records (ADRs) as concise markdown docs. Ideal for turning scattered thoughts into durable, shared project documentation.

Quality-gate review for reverse-engineering or assessment case packages. Verifies scope readiness, Evidence-to-Finding-to-Path traceability, work-item coverage, timeline consistency, and artifact hashes. Used before delivering analysis reports to ensure defensible handoff without modifying the case or target. Supports Markdown or JSON output for CI integration.

Guide for splitting extracted text into chunks for LLM context windows or RAG ingestion. Covers chunk size, overlap, markdown/yaml/semantic chunkers, tokenizer-based sizing, and the standalone chunk command.