mcaf-devex
Optimize developer experience for multi-component solutions: standardize onboarding, inner-loop, debugging, and cross-platform setup to eliminate friction and tribal knowledge.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
371 skills found
Optimize developer experience for multi-component solutions: standardize onboarding, inner-loop, debugging, and cross-platform setup to eliminate friction and tribal knowledge.
Extract and document authentic writing voice from samples. Create comprehensive voice guides for AI training, ghostwriting, and brand consistency.
Autonomous multi-agent orchestration framework for Claude Code with memory-driven workflows, parallel-first task execution, Aristotle-based deconstruction, and multi-stage quality gates.
A robust verification and QA system for software agents featuring real-time truth scoring, automated code validation, and instant rollback capabilities to maintain high reliability.
A meta-skill for building robust AI agent skills using a TDD approach: define failure (RED), implement the skill (GREEN), and plug rationalization loopholes (REFACTOR).
Implementation patterns for MERIDIAN autonomous AI agents using Claude API, including BaseAgent lifecycle, structured tool use, token budget enforcement, and cron scheduling.
Expert Rust development guide based on real-world code reviews. Ideal for idiomatic code, performance tuning, error handling, and avoiding common pitfalls in CLI and production tools.
Transforms content to match specific voice profiles, tones, or styles using configurable YAML templates for consistent brand and narrative output.
An expert-level CTF solver agent that automates reconnaissance, vulnerability analysis, and exploit generation for web, pwn, crypto, reverse, and forensic challenges.
Intelligent strategic planning and requirements gathering with multi-perspective consensus loops and structured deliberation.
A standardized template for creating and documenting modular Agent Skills to ensure consistent, efficient context engineering across AI agent systems.
Monitor and manage margin-living strategy by tracking balances, interest costs, and coverage ratios. Provides automated scaling recommendations and safety alerts based on portfolio-to-margin thresholds.