clustering_coefficients

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

No annotations are provided, so the description must carry the behavioral transparency burden. It only states the calculation and gives no details about side effects, input requirements, return format, or exceptions. This is minimal disclosure and insufficient for a full understanding of the tool's 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, concise sentence that directly states the tool's purpose without unnecessary words. Every word earns its place, and the structure is highly scannable.

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 one parameter, no annotations, and no output schema, the description must provide more context. It only states the basic calculation, omitting details about input format, return values, and usage scenarios. This makes it incomplete for an agent to confidently invoke the tool.

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 has one parameter 'graph' with no description (0% coverage), and the tool description does not explain what this parameter should contain (e.g., graph name, graph object). The description adds no meaning beyond the parameter name, leaving the agent without necessary input context.

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 'Calculate' and identifies the resource 'clustering coefficients for all nodes,' making the tool's purpose clear. However, it does not differentiate this tool from sibling centrality metrics like degree_centrality or betweenness_centrality, so it lacks the explicit sibling distinction that would earn a 5.

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?

No guidance is provided about when to use this tool versus alternatives. The description simply states what it does, with no mention of use cases, prerequisites, or exclusions, leaving the agent without decision support.

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