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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description needn't repeat those. It adds value by detailing what the templates contain: 'proper node definitions (description, flat_labels, schema with flat field definitions), relationship configurations (from, to, cardinality, data_schema), and hierarchical entity nesting.' This gives the agent a concrete preview of the response content, going beyond the safety profile provided by annotations.

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 slightly verbose, with emojis and capitalized emphasis, but it is well-structured: it starts with the core purpose, then adds the 'use first' guidance, lists template contents, enumerates available templates, and ends with a practical tip. Every sentence adds useful context, though the use of emojis and excessive emphasis could be trimmed for a cleaner agent-facing description. It is not overly long for the information conveyed.

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 has no parameters and no output schema, the description compensates by clearly explaining what the tool returns (pre-built schemas) and what they include. It also situates the tool in a workflow ('USE THIS FIRST when creating a new graph project') and provides template categories. However, it does not specify the exact data structure or return format in detail, relying on high-level descriptions like 'schema with flat field definitions' and 'data_schema'. This is sufficient for a simple read-only template getter but leaves some room for interpretation.

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 zero parameters, so the description has no parameter semantics to explain. Per guidelines, a 0-parameter tool gets a baseline of 4. The description doesn't need to add parameter details because there are none. It does mention available templates, which could hint at selection, but since there is no parameter, this does not conflict with the schema. The baseline score of 4 is appropriate.

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 function: 'Get pre-built graph template schemas for common use cases.' It specifies a specific verb ('get'), a concrete resource ('pre-built graph template schemas'), and the intended use case. It also distinguishes from sibling tools like 'get_template_schemas' by emphasizing the 'graph' context and lists specific available templates (Social Network, Knowledge Graph, Product Catalog), making the purpose unmistakable.

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 guidance: '⭐ USE THIS FIRST when creating a new graph project!' This clearly indicates when to use relative to other tools. It also instructs that templates can be used directly with 'create_graph_project' or modified, and advises studying the templates before creating custom schemas. This directly addresses when and how to use the tool versus alternatives.

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