Single tool 'create_image' with well-structured schema and clear naming. The tool starts with 'create_' verb reflecting the action (pattern:tool compliant). Input schema is fully visible in src/index.ts with comprehensive parameter validation using Zod. Description is clear and action-oriented. However, output schema is not documented in the source code, the function saves images to disk and returns file paths, but the exact response structure is not explicitly defined or commented. Error handling in the source is basic (try-catch blocks with some error messages), but recovery guidance is minimal. The tool avoids exposing secrets (OPENAI_API_KEY is injected via environment variable, not as a parameter). No composition concerns, this is a single-purpose tool.

• Document the return type explicitly. Add a comment or JSDoc showing: {success: boolean, image_paths: string[], message?: string, api_usage?: {prompt_tokens: number, completion_tokens: number}}. This lets LLMs extract paths for downstream operations.
• Add structured error responses. Instead of throwing generic errors, return {success: false, error_code: 'INVALID_PROMPT', error_message: '...', recovery_hint: 'Try shortening the prompt or removing complex descriptions'}.
• Add a 'dry_run' boolean parameter (default false). When true, validate inputs and return mock image paths without calling OpenAI's API. This lets agents plan without wasting quota.
• Expand parameter descriptions with rationale. E.g., 'quality: high = maximum detail (slower, costlier); medium = balanced; low = fast, cheaper. auto = gpt-image-1 chooses based on prompt complexity.'
• Document dependencies and prerequisites. E.g., 'Requires OPENAI_API_KEY environment variable. Output files are saved to ~/Pictures/gpt-image-1 (or GPT_IMAGE_OUTPUT_DIR if set).' This helps agents understand setup before calling the tool.