export_table

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

With no annotations, the description carries the full burden and does so thoroughly: it discloses that the document is never modified, that existing output files are refused, that output_path=None returns inline data, and how merged/nested cells behave.

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 dense but efficient, front-loading the core purpose and then covering edge behaviors. Every sentence adds meaningful information with no filler or repetition of schema fields.

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 tool is moderately complex, but the description covers output formats, merge handling, nested-table behavior, file-vs-inline output, overwrite refusal, and non-modification. Since an output schema exists, return-value details do not need to be duplicated.

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. It does: format is tied to CSV/JSON, include_merges is defined with concrete topology fields, output_path is explained with inline vs file semantics, and table_index is linked to list_tables.

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: exporting a body-level table to CSV/JSON as a rows x grid-columns matrix. It clearly distinguishes this from generic table readers like get_table or list_tables by framing the output as an export artifact.

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?

It clearly scopes usage to body-level tables found via list_tables and explains key behavioral options. It does not explicitly name alternatives or exclusions, but 'body-level' and 'list_tables index' give an agent enough context to route correctly.

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