TokRepo — Summary
TokRepo is an open registry for AI assets (skills, prompts, MCP configs, scripts, workflows) designed for agent-to-tool and agent-to-agent discovery, where AI agents can find, inspect, and install reusable capabilities using typed contracts, with no need for manual browsing.
Problem it solves: AI agents have no standard way to discover what reusable capabilities (skills, prompts, MCP configs) exist outside their current session — TokRepo provides a machine-readable registry with multiple discovery surfaces (CLI, MCP server, well-known URLs, planning-time fallback) so agents can autonomously find and install capabilities during task planning.
Distinctive trait: The only registry in the batch designed for agent-initiated discovery: agents call tokrepo agent-check "<task>" --json during planning to find relevant capabilities, and tokrepo agent-handoff --json after tasks to return improved capabilities back to the registry.
Target audience: AI agents (not just humans) performing autonomous task planning, plus developers who want a universal asset registry compatible with Claude Code, Codex, Cursor, Gemini CLI, Cline, Windsurf, and 10+ other coding agents.
Scope: This GitHub repo is a landing page pointing to three separate repos: CLI (tokrepo-cli), MCP server (tokrepo-mcp-server), and cross-platform skill (tokrepo-search-skill). The registry website is tokrepo.com.
Differs from seeds: Uniquely positioned as infrastructure rather than a methodology framework. Unlike all seeds (which provide skills/methodology), TokRepo is the registry layer that other skills frameworks would use for asset distribution — closer in architecture to npm than to superpowers or BMAD-METHOD.