check_cf_compliance

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

With no annotations, the description carries the full burden. It discloses that the tool performs basic CF checks and returns a JSON string report, which is useful. However, it does not mention side effects, error behavior, or that it is read-only, leaving some behavioral expectations unstated.

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 short and front-loaded with the purpose, followed by clearly labeled Args and Returns sections. It is efficient and easy to scan, though slightly docstring-like rather than optimized for AI agent consumption.

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?

For a simple one-parameter tool, the description covers what it does and what it returns. However, it lacks guidance on when to use it versus check_data_quality, and provides no detail about what the compliance report includes. The output schema may cover return structure, but the missing usage context keeps it from being complete.

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 0%, so the description must compensate. The Args section explicitly explains that file_path is the path to the NetCDF file, which gives meaning beyond the schema's bare type/title. This is sufficient for the single parameter.

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 identifies the operation: checking whether a NetCDF file follows CF conventions, which is a specific verb and resource. It is distinguishable from sibling tools like get_file_structure and get_variable_stats, though it does not explicitly differentiate itself from check_data_quality.

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 gives no explicit guidance on when to use this tool versus alternatives such as check_data_quality or explain_variable. It states that it performs 'basic checks', but does not say when a user should prefer this over other validation or inspection tools.

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