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Optimize prompts, code specs, and agent skill files with DSPy and MCP.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "specopt-mcp" yet — see the docs or source repo.
Analyze this agent skill file, identify prompt redundancy, unclear variable naming, and ambiguous step definitions, then produce an improved version without changing the original functionality.
Returns a diagnosis, optimization suggestions, and a revised skill file with clearer structure.
Optimize this feature specification so the requirements are clearer, edge cases are more complete, and the input-output definitions are suitable for AI agent execution.
Outputs a more rigorous specification with executable field definitions and rewrite suggestions.
I have a prompt and its related tool-calling code. Optimize them together to improve reliability, maintainability, and task completion rate, and explain the reasons for each change.
Provides an optimized prompt, code adjustment recommendations, and the impact of each change.
Input prompts and images in a GUI with Gemini-optimized AI development workflows.
Build, debug, and manage software tasks with natural language across LLMs.
Turn any OpenAPI spec into a working MCP server.
Convert any OpenAPI v3 spec into a working MCP server for AI integration.
Demo MCP server for calculations, time checks, notes, and code review prompts.
Guide spec-driven development through requirements, design, and task phases.