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. It discloses key behavioral traits: the tool returns JSON with nodes and edges compatible with graph visualizations, and it explains the two modes of operation (clusters vs. subgraph). However, it doesn't mention potential limitations like rate limits, authentication needs, or data size constraints.

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 front-loaded with the core purpose, followed by usage guidelines and output format. Every sentence earns its place, with no wasted words, making it highly efficient and easy to parse.

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 (graph generation with optional parameters) and no output schema, the description does well by explaining the output format and behavior. However, it could be more complete by detailing error cases or performance considerations, though the lack of annotations isn't fully compensated.

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 parameters thoroughly. The description adds some context by explaining the effect of 'center_note' on output, but doesn't provide additional meaning beyond what's in the schema descriptions. This meets the baseline for high schema coverage.

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: 'Generate a graph view of links between notes.' It specifies the verb ('generate') and resource ('graph view of links between notes'), and distinguishes it from siblings by focusing on graph visualization rather than backlinks, tags, reading, or writing operations.

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 explicitly states when to use this tool vs. alternatives: 'Without center_note, returns the most connected clusters. With center_note, returns the subgraph around that note.' This provides clear context for both scenarios and differentiates it from sibling tools like knowledge_backlinks or knowledge_related.

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