Browse Skills

Agent Eval compares coding agents head-to-head on reproducible tasks, measuring pass rate, cost, time, and consistency. Use it to choose between agents or validate changes with data instead of impressions.

Agent Harness Construction designs and optimizes AI agent action spaces, tool definitions, and observation formatting to improve completion rates. Use it when defining or revising an agent's tool set, action space, or observation format.

Agent Introspection Debugging guides an AI agent through a structured four-phase loop to capture failures, diagnose root causes, apply contained recovery actions, and produce an introspection report. Use it when an agent run fails repeatedly, loops, or drifts and you need a reproducible diagnosis rather than a blind retry.

Agent Payment x402 adds x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Use it when an agent must pay for APIs or services, enforce spending limits, or manage its own wallet.

Agent Self-Evaluation rates an agent's own output on five axes—accuracy, completeness, clarity, actionability, and conciseness—with evidence per criterion. Use it after completing any non-trivial task to catch omissions and surface improvements before the user has to.

Agent Sort builds an evidence-backed ECC install plan for a specific repository by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use it when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

Agentic Engineering guides agents through eval-first execution, task decomposition, and cost-aware model routing. Use it when planning or executing engineering work that agents will carry out end to end.

Agentic OS codifies a persistent multi-agent operating system architecture for Claude Code. Use it when building a multi-agent workflow with file-based memory, slash commands, and scheduled automation that survives session restarts.

AI-First Engineering defines process, review, and architecture standards for teams where AI agents produce most implementation output. Use it to set ownership rules, quality gates, and evaluation criteria for agent-generated code.

AI Regression Testing provides testing patterns for AI-assisted development, catching blind spots when the same model writes and reviews code. Use it for sandbox-mode API tests and regression coverage after AI code changes.

Android Clean Architecture provides patterns for structuring Android and Kotlin Multiplatform projects, covering module boundaries, UseCases, Repositories, and data layer with Room, SQLDelight, and Ktor. Use it when setting up layered architecture in Android or KMP projects.

Angular Developer generates Angular code and provides architectural guidance for Angular projects. Use it for creating projects, components, or services, or for best practices on reactivity, forms, DI, routing, SSR, accessibility, animations, styling, testing, and CLI tooling.