get_rows

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

The readOnlyHint annotation already covers non-destructiveness. The description adds important behavioral context beyond the annotation: filters are SQL-parameterized to prevent injection, results are capped at limit rows, the default limit is 50, and large-ish retrievals should use offset rather than raising the limit. It does not describe output shape or project redaction behavior, but the schema covers those details.

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 compact and front-loaded. The first sentence identifies purpose, the middle sentences provide operator and projection guidance, and the final sentence covers pagination semantics. It packs useful decisions into a small number of sentences without 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?

Given the readOnly annotation, 100% schema coverage, and careful parameter descriptions already presenting limit, offset, redaction, filters, and projection, the description completes the picture by explaining how an agent should compose the key parameters and when to hand summarization off to another tool. There is no formal output schema, but the schema's redaction parameter already references _meta.redaction details.

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?

The schema has 100% parameter documentation, so the baseline is roughly 3; the description still earns extra by giving higher-level guidance that the schema does not: minimal columns projection reduces tokens on wide tables, and offset should be preferred to raising the limit. The operator list is redundant with the schema enum, so it is not perfect.

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 exactly what the tool does: filtered row retrieval using structured filters. It also distinguishes itself from aggregation tools by explicitly saying to prefer aggregate() for summaries, so an agent can understand its scope and role.

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 gives actionable guidance: use columns=[] to reduce tokens, prefer aggregate() for summaries rather than paginating through rows, and page with offset instead of raising the limit. These are concrete selection and invocation rules, not just restated intentions.

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