inspect_geocroissant

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

The description discloses an important behavioral trait beyond the annotations: it will reject invalid documents via strict syntax/schema check, which is critical for an agent to know. It also details what content will be returned (core metadata, geo extension properties, distributions, record sets, fields, etc.). Since annotations are absent, the description carries the burden, and it does an above-baseline job by describing the validation side effect and return shape, though it could be even richer about error handling and conflicts among the input parameters.

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 and well structured with clear sections: the core purpose in the first line, the implementation detail in the next, an explicit 'Usage' block, and a 'Returns' section with a bulleted list. Every sentence earns its place and covers the key behavioral aspects. Front-loading is good: an agent can quickly answer 'What does this do?' and 'When do I call it?'.

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 is complete given the tool complexity: an inspection tool with three mutually-exclusive inputs and a rich output that is fully described. It even goes slightly beyond the call by describing the return dictionary structure, which combines well with the output schema already present. The only limitation is param precedence, but that is a minor gap and the overall context is fully sufficient for correct invocation.

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 100% (all three parameters have descriptions: 'URL', 'Path', 'Raw JSON string'), so the baseline is 3. The description itself does not add much insight about parameter precedence or how to choose among the three parameters when multiple are provided, which is a meaningful gap an agent would face. It relies on the schema, which is adequate but not enhanced.

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 states a specific verb and resource ('Inspects a Croissant/GeoCroissant document') and distinguishes it from siblings like validate_croissant, create_geocroissant_from_stac, and get_records_preview, which have different purposes. The mention of mlcroissant and 'strict syntax/schema check' and the structured return digest make the scope 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 explicitly names when to use this tool ('to READ and UNDERSTAND a dataset description before consuming it, comparing datasets, or planning how to load records'). It doesn't list exclusions, but the ' 'Usage' sentence plus the sibling context provides clear enough guidance for an agent to select it over the alternative creation/validation/search tools.

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