Knowledge Assistant MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool 'Returns matching notes with snippets,' which gives some insight into output behavior. However, it lacks details on permissions needed, rate limits, error handling, or whether results are paginated. For a search tool with no annotation coverage, this leaves significant gaps in understanding how it behaves in practice.

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 extremely concise and front-loaded: two sentences that directly state the action and result. Every word earns its place, with no redundant or vague language. It efficiently communicates the core functionality without unnecessary elaboration, making it easy for an AI agent to parse quickly.

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 moderate complexity (search with two parameters) and no annotations or output schema, the description is minimally adequate. It covers the basic purpose and output format ('matching notes with snippets'), but lacks details on behavioral traits, usage context, and deeper parameter insights. For a search tool, this leaves room for improvement in guiding effective use, though it meets the bare minimum for understanding.

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?

The input schema has 100% description coverage, with clear documentation for both parameters ('query' and 'max_results'). The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain query syntax, ranking, or snippet generation. Since the schema already does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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's purpose: 'Search notes in the Knowledge vault by content or title.' It specifies the verb ('Search'), resource ('notes in the Knowledge vault'), and scope ('by content or title'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from siblings like 'knowledge_explore_tag' or 'knowledge_graph', which might also involve searching or exploring notes.

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 no guidance on when to use this tool versus alternatives. With siblings like 'knowledge_explore_tag' (likely tag-based exploration), 'knowledge_graph' (graph-based queries), and 'knowledge_related' (finding related notes), there's no indication of when this content/title search is preferred over other search or exploration methods. The description only states what it does, not when it's the right choice.

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