Skill Claude CodeCodex
Skill that instructs an agent to execute a plan.md task list using strict test-driven development — Red, Yellow, Green phases — one task at a time, verifying tests pass before moving on.
Skill Claude CodeCodex
Skill that instructs an agent to turn a research.md file into a test-driven, task-by-task implementation plan — structured so any downstream LLM agent can pick up individual tasks and execute them independently.
Skill Claude CodeCodex
Skill that instructs an agent to deeply explore a codebase in response to a user query — mapping current implementation, identifying impacted areas, and gathering everything needed for a downstream implementation agent.
Skill Claude CodeCodex
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics.
Skill Claude CodeCodex
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
Skill Claude CodeCodex
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports.
Skill Claude CodeCodex
Add x402 payment execution to AI agents — per-task budgets, spending controls, and non-custodial wallets via MCP tools. Use when agents need to pay for APIs, services, or other agents.
Skill Claude CodeCodex
Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.
Skill Claude CodeCodex
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
Skill Claude CodeCodex
Engineering operating model for teams where AI agents generate a large share of implementation output.
Skill Claude CodeCodex
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.