graph_stats

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It reveals that the tool returns counts and load warnings, and the verb 'Counts' implies a read-only operation. However, it does not explain the meaning of load warnings, potential performance cost, or failure behavior.

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 a single efficient sentence that front-loads the core purpose and includes the most important output dimensions. Every word adds useful information, with no repetition or filler.

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?

With no parameters and a simple aggregation task, the description covers the main invocation needs. The lack of an output schema means the exact return format is unspecified, but the description names the aggregation dimensions and the warning feature, leaving only minor gaps.

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 tool has zero parameters, so there are no parameter semantics to document. Baseline 4 applies because invocation requires no arguments and the schema already confirms this.

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 uses a specific verb ('Counts') and identifies the resource (graph statistics) with clear aggregation dimensions: node type, link type, and source. It also distinguishes this tool from siblings like get_graph and list_types by focusing on aggregate counts and load warnings rather than raw graph data or type lists.

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 about when to choose graph_stats over its siblings such as get_graph, list_types, or neighbors. No context, exclusions, or alternative conditions are given, so an agent must infer the appropriate use case.

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