knowledgelib-mcp

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds useful workflow context (discovery phase before querying) and hints at return content (unit counts), but omits details about pagination, caching, or response format that would help the agent handle the output.

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?

Two sentences with zero waste. The first front-loads the action and resource; the second provides usage context. Every word earns its place with no redundancy or tautology.

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?

Given the tool's simplicity (no parameters, read-only annotations) and lack of output schema, the description adequately covers the essential information: what it returns (domains with unit counts) and why to use it (discovery). It appropriately compensates for missing output schema by describing the payload content.

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?

With zero parameters, the baseline score per rules is 4. The schema is empty (100% coverage of nothing), and the description appropriately focuses on behavior rather than inventing parameter documentation where none exists.

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 provides a specific verb ('List'), clear resource ('knowledge domains'), and scope detail ('with unit counts'). It effectively distinguishes this discovery tool from siblings like query_knowledge and batch_query by emphasizing the enumeration of available topics.

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 second sentence ('Use this to discover what topics are covered before querying') provides clear context for when to invoke the tool relative to sibling query tools. However, it could be strengthened by explicitly naming the query siblings (query_knowledge, batch_query) rather than using the generic term 'querying'.

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