productivity▌

Fast, Rust-based linter and formatter replacing ESLint and Prettier with 100x speed improvement. \n \n Single tool combining linting, formatting, and import sorting with zero-config defaults and TypeScript-first design \n Supports three core commands: check (lint + format together), format (formatting only), and lint (linting only), all with --write for automatic fixes \n Includes VS Code extension with format-on-save, organized rule categories (correctness, style, suspicious, performance, secur

Generate engaging, localized release notes from flexible input. Optionally pair with promotional text updates.

Delegate specialized tasks to isolated AI assistants with custom tools, models, and system prompts. \n \n Sub-agents preserve main context by isolating verbose tool outputs and intermediate reasoning, enabling longer sessions and cleaner conversations \n Three built-in agents available: Explore (Haiku, read-only codebase search), Plan (Sonnet, plan-mode research), and General-Purpose (Sonnet, full read/write access) \n Create custom agents in .claude/agents/ with YAML frontmatter and markdown pr

Every browser automation follows this pattern:

"Work like Manus" — Uses persistent markdown files for planning, progress tracking, and knowledge storage.

Spring Data Neo4j integration for graph databases with repositories, Cypher queries, and reactive operations. \n \n Three abstraction levels: Neo4j Client (low-level), Neo4j Template (medium-level), and Neo4j Repositories (high-level query derivation) \n Supports both imperative Neo4jRepository and reactive ReactiveNeo4jRepository patterns; do not mix both in the same application \n Entity mapping with @Node and @Relationship annotations, supporting business keys or generated IDs with immutable

$21

Curated collection of role-based, task-specific, and analytical prompt templates for common development workflows. \n \n Includes 15+ ready-to-use prompts across categories: expert developer, code reviewer, technical writer, system architect, debugging, refactoring, testing, and security review \n Covers prompt engineering techniques like chain-of-thought, few-shot learning, persona patterns, and structured output formatting \n Provides a prompt improvement checklist covering objective clarity,

Comprehensive guide for creating modular skills that extend Codex's capabilities with specialized knowledge and workflows. \n \n Skills consist of a required SKILL.md file with YAML frontmatter (name, description) and optional bundled resources (scripts, references, assets) organized to manage context efficiently \n Follow a six-step creation process: understand concrete usage examples, plan reusable contents, initialize with init_skill.py, edit SKILL.md and resources, package with package_skill

Turn any identifier into a full contact dossier. The user provides identifying info via "$ARGUMENTS".