Plain MCP server has 7 tools with basic schemas and descriptions, but significant gaps prevent higher scores. All tools have descriptions (10-100 chars, mostly adequate) and input schemas with type definitions. However, parameter descriptions are minimal or absent in several tools (e.g., fetch_url lacks maxBytes description). No output schemas are documented, critical for LLM planning. Error handling is not visible in the provided code. Tool naming follows verb_noun convention (generate_*, edit_*, fetch_*) which is good, but composition issues exist: generate_deck, generate_doc, generate_sheet are near-duplicates with minimal differentiation. The edit_* tools require currentSource as a string parameter rather than accepting resource URIs or IDs, forcing agents to manage source state externally. No evidence of idempotency, pagination, or recovery guidance in tool definitions.

• Document output schemas for all 7 tools. Specify what fields are returned (e.g., generate_deck returns {artifact_id, slides[], layout, content}). Include field types and descriptions so LLMs can chain results.
• Add descriptions to all parameters. For fetch_url.maxBytes, specify range (e.g., '1-10485760 bytes, default 1MB'). For edit_* tools, clarify currentSource format (markdown, JSON, or raw text) and expected structure.
• Consolidate generate_* tools or add clear differentiation. If all three are needed, explain when to use each (e.g., 'Use generate_deck for presentations, generate_doc for reports, generate_sheet for data analysis'). Consider a single parameterized tool.
• Refactor edit_* tools to accept resource IDs or URIs instead of raw source strings. Implement server-side source resolution via getSource() hook (already in ToolContext). This reduces agent state management and token waste.
• Add error handling guidance. Document which errors are retryable (network timeout, rate limit) vs user-fixable (invalid intent, unsupported mode). Include recovery hints: 'If generation fails, try a shorter intent or different mode.'