Technical Writing

My personal best practices for writing clear and effective code comments.

Use when turning a documentation link or article into spaced-repetition flashcards - fetches and extracts core ideas, compares against existing cards/notes, right-sizes output by source density and existing coverage, updates only incorrect/outdated cards, and creates missing cards with strict citation, slug, and tag rules

Maintain and update architecture documentation in docs/architecture/. Uses tool-based inspection first, falling back to CLI only when needed.

Use when saving notes to Obsidian vault, creating documentation, capturing knowledge, or logging any information. This skill determines the correct PARA location and applies the appropriate template from the vault.

Maintain living documentation with single source of truth approach, journal reconciliation, and worklog.db integration

Use this skill when starting a new project or adding SynthesisFlow to an existing project. Scaffolds the directory structure (docs/specs, docs/changes) and configuration files needed for the spec-driven development workflow.

QA engineer and test automation specialist with deep expertise in Flutter testing. Use for designing test strategies, writing unit/widget/integration tests, improving test coverage, and ensuring code reliability.

Convierte archivos Markdown a DOCX con formato profesional usando pandoc. Incluye portada con título, tabla de contenidos, cabeceras y estilos corporativos. Usar cuando se necesite generar documentos Word desde Markdown, exportar documentación, o crear informes en formato .docx.

Эксперт по копирайтингу. Используй для написания продающих текстов, заголовков, landing pages и conversion copy.

Create, update, and review code-map and spec documents for features. Use this skill to document code execution flows, trace function calls, and maintain architectural documentation in docs/2-current/.

Find and add authoritative source links for all facts, citations, and references in markdown documents

Generates high-quality documentation for code, including inline comments, function docstrings, and README files. It ensures consistency in tone, format, and detail level.

This skill should be used proactively before writing any Scala code for the first time in a session. It ensures all Scala code adheres to project-specific coding standards, formatting rules, naming conventions, and architectural patterns defined in the comprehensive style guide. Trigger this skill when about to write Scala classes, traits, objects, or modify existing Scala files.

Orchestrator agent that coordinates all BarqNet specialized agents (backend, integration, client, documentation, audit, testing) to execute complete end-to-end workflows. Plans multi-agent deployments, manages task dependencies, tracks progress across all platforms, and ensures comprehensive completion. Use for complex multi-component tasks, full-stack features, or production deployments.

Enterprise CLI patterns using oclif framework with TypeScript. Use when building oclif CLIs, creating plugins, implementing commands with flags/args, adding auto-documentation, testing CLI commands, or when user mentions oclif, enterprise CLI, TypeScript CLI, plugin system, or CLI testing.

Generate AI-optimized context for NuGet packages using Repomix. Use when preparing AI docs, API references, or dependency analysis ("nuget context", "repomix nuget").

Generates clear, conventional commit messages from git diffs. Use when writing commit messages, reviewing staged changes, or when the user asks for help with git commits.

This skill should be used when writing test cases, fixing bugs, analyzing code for potential issues, or improving test coverage for JavaScript/TypeScript applications. Use this for unit tests, integration tests, end-to-end tests, debugging runtime errors, logic bugs, performance issues, security vulnerabilities, and systematic code analysis.

Lightning-fast DataFrame library written in Rust for high-performance data manipulation and analysis. Use when user wants blazing fast data transformations, working with large datasets, lazy evaluation pipelines, or needs better performance than pandas. Ideal for ETL, data wrangling, aggregations, joins, and reading/writing CSV, Parquet, JSON files.

Orchestrates autonomous development workflows through specialized character-based phases - research (Lisa), complexity assessment (Mayor Quimby), planning (Professor Frink), documentation (Martin Prince), implementation (Ralph), and quality validation (Comic Book Guy). Handles multi-step development tasks end-to-end with automatic error recovery, kickback routing, and iterative refinement. Use for complex feature development, bug fixes requiring investigation, or any task benefiting from structured research-plan-implement-validate cycles.