EKMS MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It explains search mode behaviors (e.g., semantic understands intent but may miss exact matches) and mentions knowledge graph inclusion via includeRelated parameter. However, it doesn't disclose critical behavioral traits like pagination, rate limits, authentication needs, error handling, or what the output looks like (no output schema).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with bullet points for search modes and knowledge types, making it easy to scan. It's appropriately sized for a tool with 6 parameters, though the knowledge type list is somewhat lengthy. Every sentence earns its place by explaining functionality without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a search tool with 6 parameters and no output schema, the description provides good context about search modes and knowledge types but has significant gaps. It doesn't explain the output format, result ordering, pagination, error cases, or how it differs from sibling tools like recommend_knowledge. With no annotations and no output schema, more behavioral context would be helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds some value by explaining the trade-offs between search modes and listing knowledge types, but doesn't provide additional semantic context beyond what's in the schema descriptions (e.g., how customerName filtering works, what 'related knowledge' means). Baseline 3 is appropriate when schema does heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches an enterprise knowledge base, specifying the verb 'search' and resource 'knowledge base'. It distinguishes itself from siblings like get_knowledge_item (retrieves specific items) and recommend_knowledge (suggests content) by focusing on query-based searching across multiple knowledge types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use different search modes (hybrid, semantic, keyword) based on trade-offs, but doesn't explicitly mention when to use this tool versus alternatives like recommend_knowledge or get_knowledge_graph. It lists knowledge types but doesn't guide on when to filter by them versus using list_knowledge_types first.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.