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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses truncation behavior (responses capped near 20KB, columns capped at 50, version_keys limited to the newest 3), the truncated/more fields that let the agent recover cut data, and the deleted/alternatives path for removed IDs. These are exactly the behavioral traits an agent cannot infer from structured fields.

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?

It is dense but well front-loaded: purpose first, then the return payload, then the truncation caveat, then the operation narrowing and next-step pointer. The long enumeration of return fields is somewhat redundant given an output schema exists, but it does double as disclosure of the truncation surface.

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 two-parameter read tool with full annotations and an output schema, the description covers the remaining unknowns well: response size limits, how to drill into one operation, what happens for deleted IDs, and the follow-up with get_preview. Only the id vs dataset_id naming slip and the unaddressed fields/record overlap keep it short of 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 coverage is 0%, so the description carries the burden and mostly does: it explains that operation accepts a function name or operation_seq and is used to view a single operation in full, and dataset_id is implicitly the dataset selected from search. The only blemish is that it writes 'show(id, ...)' while the actual parameter is dataset_id, a small naming mismatch.

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 gives a concrete verb and resource: view the structure and access methods of a dataset chosen from the datagokr search, and it names get_preview as the tool for actual row data. It does not, however, differentiate itself from siblings like fields or record, which sound like they could also return schema-like information, so the agent must guess at that boundary.

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 states a clear next-step alternative ('if it looks usable, check real rows with get_preview') and explains how to narrow an oversized API response via the operation parameter. It also covers the deleted-ID case with alternatives. What is missing is explicit guidance on when to use show instead of fields or record.

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