llm_model_export

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

No annotations are provided, so the description must fully disclose behavior. It mentions exporting a file and returning path/count, but does not state if the operation is read-only, whether it overwrites existing files, or any potential side effects. The behavioral information is incomplete.

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 concise with two paragraphs, including an Args/Returns section. Every sentence adds value without redundancy, and it is front-loaded with the core purpose.

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?

The description covers the essential aspects for a simple export tool: what it does, the format parameter, and return values. Given the presence of an output schema (though not shown), the description is sufficiently complete. Minor gap: no mention of the file destination or naming.

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 description adds meaning beyond the input schema by explicitly explaining the 'format' parameter with allowed values (csv, json) and default. Since schema description coverage is 0%, this explanation is necessary and well-provided.

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 exports model tracking data (routing history) for external analysis, using verbs like 'Export' and specifying the resource. It stands out among siblings as the only export tool for model data, but could be more precise about what 'model tracking data' entails.

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 explicit guidance on when to use this tool versus alternatives. While it mentions 'for analysis in spreadsheets or data tools', it does not address when not to use it or provide comparisons to related tools like llm_model_usage or llm_model_eval.

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