Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides Codex CLI execution helpers, and enables seamless interoperability between both tools
WHAT YOU BECOME
Perfect for these scenarios
Create interactive CLI tools for dynamic config file generation with validation.
Guide users through secure authentication setup with password prompts.
Build intuitive CLI installers with progress bars and error handling.
Design user-friendly CLI forms with placeholders and real-time validation.
MEASURED GAIN
Proven benefits and measurable impact
Reduce time spent building CLI forms with pre-built validation components.
Enhance user experience with browser-like CLI forms and real-time feedback.
Minimize user mistakes with built-in validation and placeholder text.
WHAT YOU GET
Files, tags and the three-step install
Tip: Read the documentation and the code before first use, so you know what it does and which permissions it needs.
NEXT SCRIPTS
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Claude Code agent generation system that creates custom agents and sub-agents with enhanced YAML frontmatter, tool access patterns, and MCP integration support following proven production patterns
Generate and maintain AGENTS.md files following the public agents.md convention. Use when creating documentation for AI agent workflows, onboarding guides, or when standardizing agent interaction patterns across projects.
Validate OpenAPI, Swagger, and GraphQL schemas match backend implementation. Detect breaking changes, generate TypeScript clients, and ensure API documentation stays synchronized. Use when working with API spec files (.yaml, .json, .graphql), reviewing API changes, generating frontend types, or validating endpoint implementations.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.