This Spring AI MCP server exposes 5 course management tools with HTTP transport. Critical issues: (1) Tool names lack action verbs, 'addNewCourse', 'removeCourseById', 'updateCourseByCourseId' are awkward; 'getAllCourses' and 'getCoursesByTitle' partially qualify. Production tools favor verb_noun (create_course, delete_course, update_course, list_courses, search_courses). (2) Descriptions are present but terse (avg 85 chars, below the 194-char baseline for A+ tools). Examples: 'Add a new course with the given title and description' lacks context on return value, data constraints, or when to use it vs alternatives. 'Get the list of all the available courses whose courseTitle matches with the provided courseTitle' is redundant and doesn't explain input format or result limits. (3) All 5 tools have basic input schemas with type and description for parameters, which is positive. However, no output schemas are documented, the LLM cannot predict what fields will be returned, breaking the composition pattern. (4) Error handling is minimal; descriptions do not guide recovery (e.g., 'If no course is found, return 'Course doesn't exist'' is a vague spec, not an error handling pattern). (5) Destructive and write operations (removeCourseById, updateCourseByCourseId) rely on a 'userConfirmed' boolean parameter to prevent accidents, an anti-pattern. Per pattern:confirmation-request, a better design would be two separate tools (e.g., confirm_course_removal + execute_removal) or a dry-run parameter. (6) Parameter naming is inconsistent: courseTitle, courseId, userConfirmed mix camelCase and use type suffixes. (7) No evidence of pagination for list operations, getAllCourses returns all courses with no limit or offset, risking context window exhaustion. (8) Schemas visible in the tool definitions, but no response structure documented for any tool. Average per-tool score: 42 (range 30 - 55).

• Rename tools to verb_noun: create_course, list_courses, search_courses, delete_course, update_course. This matches production baselines and lets LLMs infer intent from names alone.
• Document output schema for every tool. Specify which fields are returned (id, title, description, created_at, updated_at, etc.) with types and descriptions. Enable LLM to plan downstream calls.
• Expand descriptions to 150 - 200 characters. Answer: What does it do? When to use it vs similar tools? What does it return? Example: 'Create a new course with a title and description. Returns the course_id, title, description, and creation timestamp. Use before enrolling students.'
• Add pagination to getAllCourses: accept limit (default 20, max 100) and offset parameters. Return total count and next_offset. Document the limit in the description.
• Replace userConfirmed boolean pattern with two-phase confirmation. Offer a preview/dry-run tool (preview_course_deletion, preview_course_update) that returns what would change, then a separate execute tool. Or implement Multi Round-Trip Requests (MRTRs) with input_required result to ask the user inline.
• Add error recovery guidance: 'If course not found, the getCoursesByTitle tool searches by partial name match and may find similar courses. Call that first if you only have a title fragment.'
• Standardize parameter naming: use courseId (not courseId mixed with course_id). Consider userConfirmed → confirmation or skip this entirely by splitting confirmation into a separate tool.