check_nested_structure

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It thoroughly explains the walk over nested STRUCT/LIST schema, the exact rows/fields inspected, the 80% presence threshold, the DuckDB JSON fallback meaning type drift, and the returned SQL. This is exemplary transparency.

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 three compact, well-structured sentences. The first sentence states purpose, the second enumerates output details, and the third explains flags and return value. There is no redundancy 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 an output schema and only two parameters, the description covers purpose, outputs, thresholds, and type-drift interpretation thoroughly. The only notable gap is the undocumented sample parameter, preventing a perfect score.

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%, and the description never mentions source_id or sample. While source_id is inferable from the name, sample (the number of rows to inspect) is completely undocumented, so the description fails to compensate for the lack of parameter documentation.

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 action ('walk the nested STRUCT/LIST schema' for JSON-loaded sources) and names concrete outputs: leaf-path type, presence percentage, type-drift/sparse flags, and a paste-ready flatten SQL. It clearly distinguishes itself from generic tools like describe_source or check_arrays.

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 opening 'For JSON-loaded sources' provides a clear context for when to use this tool. It does not explicitly name alternative tools or when not to use it, but the intended scope is evident. This is 'clear context, no exclusions' rather than a full alternatives comparison.

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