Knowledge Graph 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. While it describes graph types and design guidelines, it does not disclose critical behavioral traits such as whether creation is idempotent, what permissions are required, how errors are handled, or what the response looks like. For a creation tool with zero annotation coverage, this is a significant gap in transparency.

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 appropriately front-loaded with the core purpose, but it becomes lengthy with detailed design guidelines for six graph types. Some sentences, like the repetitive 'Recommended to...' patterns, could be condensed. While informative, the structure could be more concise without losing essential context.

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 complexity of creating knowledge graphs with multiple types, no annotations, and no output schema, the description is partially complete. It covers graph types and design guidelines well but lacks details on behavioral aspects, error handling, and response format. For a tool with 3 parameters and no structured safety hints, more comprehensive context would be beneficial.

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 33% (only the 'type' parameter has a description). The description compensates by elaborating on the 'type' parameter with detailed guidelines for each graph type, adding substantial meaning beyond the schema's enum values. However, it does not provide semantics for 'name' or 'description' parameters, leaving them partially undocumented.

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 explicitly states the tool's purpose: 'Create a new knowledge graph.' It distinguishes this tool from siblings like add_node, add_edge, or list_graphs by focusing on initial graph creation rather than modification or querying. The description provides specific details about supported graph types, making the purpose clear and distinct.

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 this tool by detailing six graph types and their recommended design guidelines. However, it does not explicitly state when not to use this tool or mention alternatives like update_resource or save_resource for modifying existing graphs. The guidelines are helpful but lack explicit exclusions or comparisons to sibling tools.

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