Server has 5 tools with complete input schemas and descriptions. Naming follows verb_noun convention (read_, write_, append_, replace_, list_). Descriptions are present (avg ~100 chars) but lack actionable context for LLM selection. Parameters are typed and mostly described, but lack constraints (enums, ranges, format hints). Output schemas are not documented, LLMs cannot predict response structure. Error handling is absent from visible code. No tool annotations (readOnlyHint, destructiveHint). write_docx and append_to_docx accept base64 image data but lack validation guidance or size limits.

• Document output schemas for all tools. E.g. read_docx returns {paragraphs: [{text: string}], images: [{id: string, width: number, height: number, base64: string}]}. LLMs need this to plan downstream calls.
• Add tool annotations: mark read_docx and list_docx_images with readOnlyHint=true; mark write_docx, append_to_docx, replace_text_in_docx with destructiveHint=true. This signals to LLMs which tools have side effects.
• Enhance parameter descriptions with constraints. E.g. 'width (number, 0.5 - 11 inches, default 4)' and 'image_data (base64-encoded PNG/JPEG, max 10MB)'. Add enum for content[].type if other types may be added.
• Implement error handling that guides recovery. E.g. 'File not found at {file_path}. Check the path and try again.' or 'Invalid base64 image data. Ensure image_data is valid base64-encoded PNG or JPEG.'
• Expand tool descriptions to clarify intent and distinguish overlapping tools. E.g. 'read_docx: Extract full document text and images. Use this to review or analyze a document. list_docx_images: List image metadata only (IDs, dimensions). Use this to find specific images without loading full text.'

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry