Write, refactor, and ship code with an agent that knows your stack.
Most artifacts in the catalog live here: tools that read a codebase, follow its conventions, and make changes you would not be embarrassed to review. Expect language-specific helpers, refactoring workflows, spec-driven development harnesses, and framework-aware assistants for stacks like React, Next.js, Python, Rust, and Go. If you want your agent to stop writing generic code that ignores how your project actually works, start here.
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The Open Standard for Generative UI
Generate, preview, save, or validate Preline theme CSS using the bundled local generator in this skill. Use when the user asks to create a new Preline theme, match a brand color, translate a mood into a theme, generate light and dark theme CSS, preview theme output without writing files, or review and fix generated theme tokens. Do not use for generic non-Preline CSS work or arbitrary command execution.
MCP server for terminal operations and file editing
Generate well-formatted git commit messages following conventional commit standards
jscpd server application
AI-powered terminal assistant that understands your codebase, edits files, runs commands, and automates development workflows.
Self-improving AI workflow system. Crystallize requirements before execution with Socratic interview, ambiguity scoring, and 3-stage evaluation.
scrape data from Google Maps.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
OpenAgentsControl — multi-agent orchestration for Claude Code. Context-aware development with skills, subagents, parallel execution, and automated code review.
Autonomous game development for Godot and Bevy with Claude Code and Codex
Analyze codebases and automatically generate architecture diagrams, flowcharts, and org charts. Uses AST parsing to map import dependencies for Python, JS/TS, Go, and Java, outputting Mermaid or SVG files. Triggered when users ask to visualize code architecture, understand dependencies, draw a flowchart, or create a module diagram from source code.
Caching strategies — invalidation, TTL guidelines, cache keys, cache layers, and when not to cache. Use when implementing or reviewing caching logic.
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules. Use when user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more AI-navigable.
React composition patterns that scale. Use when refactoring components with
Code refactoring workflow - analyze → plan → implement → review → validate
Fast codebase search via WarpGrep (20x faster than grep)
Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support
Create and use Claude Code slash commands - quick prompts, bash execution, file references
Fast file editing via Morph Apply API (10,500 tokens/sec, 98% accuracy)
Quickly deslop UI code by fixing spacing, hierarchy, typography, and small layout issues. Use when the interface needs a fast cleanup or polish pass.
Deterministic router for math cognitive stack - maps user intent to exact CLI commands
Document the codebase comprehensively
Generate production Go CLIs from API descriptions or OpenAPI specs
Token-efficient code analysis via 5-layer stack (AST, Call Graph, CFG, DFG, PDG). 95% token savings.
Analyze brownfield codebase and create initial continuity ledger
Add or extend coding-agent support in cc-sdd by executing the SOP in docs/cc-sdd/sop-new-agent.md end-to-end. Use when introducing a new agent, adding a subagent-capable variant, or evaluating migration of an existing supported agent to skills-based templates.
Implementation and refactoring agent using TDD workflow
Meta-skill for internal codebase exploration at varying depths (quick/deep/architecture)
Discovers and injects project-specific coding guidelines from .trellis/spec/ before implementation begins. Reads spec indexes, pre-development checklists, and shared thinking guides for the target package. Use when starting a new coding task, before writing any code, switching to a different package, or needing to refresh project conventions and standards.
Find unused functions and dead code in the codebase
AST-based code search and refactoring via ast-grep MCP
Deep bug analysis to break the fix-forget-repeat cycle. Analyzes root cause category, why fixes failed, prevention mechanisms, and captures knowledge into specs. Use after fixing a bug to prevent the same class of bugs.
Create git commits with user approval and no Claude attribution
Braintrust tracing for Claude Code - hook architecture, sub-agent correlation, debugging
Guides collaborative requirements discovery before implementation. Creates task directory, seeds PRD, asks high-value questions one at a time, researches technical choices, and converges on MVP scope. Use when requirements are unclear, there are multiple valid approaches, or the user describes a new feature or complex task.
Captures executable contracts and coding conventions into .trellis/spec/ documents. Use when learning something valuable from debugging, implementing, or discussion that should be preserved for future sessions.
Context Engineering for AI Agents — 81 MCP tools, 10 read modes, 95+ shell patterns, tree-sitter AST for 27 languages. Compresses LLM context by up to 99%. Use when reading files, running shell commands, searching code, or exploring directories. Auto-installs if not present.
Comprehensive quality verification: spec compliance, lint, type-check, tests, cross-layer data flow, code reuse, and consistency checks. Use when code is written and needs quality verification, before committing changes, or to catch context drift during long sessions.
Understand and customize the local Trellis architecture inside a user project. Use when modifying .trellis plus platform hooks, settings, agents, skills, commands, prompts, or workflows generated by trellis init.
LeanCTX — the Context OS for AI coding agents. One local binary that compresses, remembers, routes, and verifies every token between your code and the model. No Rust required.
MCP server that gives AI assistants like Claude access to LinkedIn profiles, companies, and job postings through the user
Search arXiv papers, download full text, follow citations, and run local semantic search.
Official Claude plugin for Dart and Flutter that installs Flutter/Dart Skills and Dart MCP server for building natively compiled, visually stunning applications for mobile, web, desktop, and embedded devices from a single codebase
GhidraMCP bridge — a thin MCP↔HTTP multiplexer exposing Ghidra reverse-engineering tools to AI clients.
Claude Skills meta-skill: extract domain material (docs/APIs/code/specs) into a reusable Skill (SKILL.md + references/scripts/assets), and refactor existing Skills for clarity, activation reliability, and quality gates.
Butterbase agentic AI runtime