Skill UI

Automates the creation of deprecation notices for technical documentation, guiding users through patterns, best practices, and validation steps when writing API docs, user guides, or architecture notes.

This comprehensive guide teaches the best practices for writing effective, blameless postmortem reports following technical incidents. It provides a structured approach to documenting timelines, conducting root cause analysis (RCA), identifying systemic failures, and creating actionable follow-up items. Mastering this skill is crucial for fostering organizational learning and preventing future service disruptions.

A comprehensive collection of battle-tested, structured prompts designed to elevate interactions with Large Language Models (LLMs). Covers advanced use cases including expert coding reviews, system architecture design, performance analysis, technical writing, and creative brainstorming, ensuring high-quality, actionable AI output.

Defines a Markdown/Mermaid-first documentation skill for scientific and technical writing, providing diagram standards, 24 reference types, and templates so every report, README, or analysis stays text-first, versionable, and visualization-ready.

This skill enforces Sentry's rigorous blog writing standards, ensuring all content—from deep technical dives to product announcements—reads like it was written by a senior developer. It guides users on adopting a specific, opinionated, and technically credible voice, structuring posts around problem-solving, and avoiding generic corporate jargon.

This skill provides deep technical expertise regarding the DWARF debugging format (v3-v5) and the DWARF standard. It assists in analyzing, parsing, verifying, and generating debug information from compiled binaries. Use cases include answering questions about the DWARF specification, writing code that interacts with DWARF data, and utilizing tools like `dwarfdump` or `readelf` for structural validation and quality metric extraction.

A comprehensive guide for writing, reviewing, and structuring technical documentation for Go projects. It covers best practices for godoc comments, READMEs, contribution guidelines, and changelogs, ensuring documentation is accurate, discoverable, and tailored for both human readers and AI agents. Applicable to both libraries and CLIs.

An advanced technical writer specializing in creating structured, high-quality software documentation. This skill strictly adheres to the Diátaxis Framework, ensuring content is categorized into Tutorials (learning), How-to Guides (problem-solving), Reference (technical details), and Explanations (concept understanding). It follows a rigorous workflow: clarification, structure proposal, and content generation, guaranteeing clarity, accuracy, and user-centricity.

A comprehensive skill for creating scientific and technical documentation using Markdown and embedded Mermaid diagrams. This method establishes diagrams as text-based sources of truth, ensuring clean version control via Git diffs, native rendering across platforms (GitHub, Notion), and compatibility with AI tools, making it superior to static images.

This core skill is designed for generating complete, publication-ready scientific manuscripts. It guides users through a rigorous two-stage process: first, creating structured outlines using deep research lookup, and second, converting these into flowing, authoritative prose. It supports IMRAD structure, advanced citation formatting (APA, AMA, Vancouver), and mandatorily integrates complex visual elements like graphical abstracts and technical schematics, ensuring the final output meets high journal submission standards.

This guide outlines the rigorous structure and technical requirements for drafting comprehensive 'embodiment descriptions' within patent specifications. It instructs users on how to detail methods, systems, and variations to teach a Person Having Ordinary Skill In The Art (POSITA) how to make and use the invention. Crucially, it emphasizes describing the 'how' (structure and process) and strictly prohibits the inclusion of empirical data, accuracy percentages, or performance test results.

This tool generates a comprehensive and legally compliant patent specification document. It takes primary inputs—such as drafted claims and invention disclosures—and structures the full document, including the title, technical field, background, summary, detailed description, and abstract. It supports various international jurisdictions (CN, US, EP), ensuring the output meets rigorous patent drafting standards.