Knowledge Graph 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 of behavioral disclosure. It effectively describes the tool's dependency on list_graphs, outlines four specific use cases, and details the return data structure. However, it doesn't mention potential error conditions, rate limits, or authentication requirements.

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 clear sections (Use cases, Usage recommendations, Return data) and front-loads the core purpose. While comprehensive, some redundancy exists between the initial statement and later sections, preventing a perfect score.

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 complexity (dependency on another tool, detailed return structure) and absence of both annotations and output schema, the description provides complete contextual coverage. It explains prerequisites, use cases, usage workflow, and detailed return format, compensating for the lack of structured metadata.

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 schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description reinforces that parameters 'must be obtained from list_graphs response' but doesn't add significant semantic value beyond what's in the schema descriptions. This meets the baseline expectation 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 with a specific verb ('Get detailed information') and resource ('about a specific node in the graph'). It distinguishes this read operation from sibling tools like update_node, delete_node, and add_node by focusing on retrieval rather than modification.

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 explicit usage recommendations with step-by-step instructions, including when to use this tool ('First call list_graphs to get the node list') and how to obtain required parameters. It clearly positions this tool as dependent on list_graphs for parameter acquisition.

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