Strong foundation with 23 well-named tools following verb_noun convention (list_, get_, create_, update_, delete_, search_). All tools have descriptions (avg ~120 chars, within 10-1024 baseline). Input schemas present with types and descriptions for all parameters. Key strengths: clear naming, consistent parameter documentation, pagination support (limit/offset). Gaps: output schemas not formally documented; error handling lacks recovery guidance; no tool annotations (readOnlyHint/destructiveHint); some descriptions could be more LLM-optimized (e.g., 'Read one workspace' vs 'Retrieve workspace configuration including tools and settings').

• Add formal output schemas to all tools. Document return types as JSON Schema (e.g., {type: 'object', properties: {id: {type: 'string'}, title: {type: 'string'}, ...}}). This enables LLMs to plan multi-step chains and extract the right fields.
• Implement tool annotations: add readOnlyHint=true to all list_*, get_*, search_* tools; add destructiveHint=true to all delete_* tools. Expose via MCP's tool definition metadata so clients can warn users before destructive calls.
• Enhance error messages with recovery guidance. Replace 'raise ToolError(str(exc))' with structured errors: 'ATLAS is unreachable at {base_url}. Check network connectivity or verify base_url in config. Call atlas_status() to diagnose.'
• Add confirmation/dry-run support for destructive operations. Implement a pattern where delete_* tools accept a 'confirm=false' parameter (default). When false, return 'Would delete X. Call again with confirm=true to proceed.' This prevents accidental data loss.
• Expand parameter descriptions to 50-200 chars with LLM-optimized context. E.g., 'Filename (must end in .md and be directly inside prompts_dir to prevent directory traversal attacks). System prompts are loaded on ATLAS startup.' This guides LLM reasoning and security awareness.