Read Cleaned KoboToolbox Rows

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds meaningful behavior beyond those: rows are cleaned, labels replace codes, the query is a Mongo-style server-side filter, and output can be markdown or JSON. It doesn't cover auth or error behavior, but the annotation base makes that a minor gap.

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 well-ordered: purpose first, then usage guidance, then a concise Args list. Every sentence earns its place and no filler or repetition of annotations is present.

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 read-only sampling tool with full schema coverage, the description covers the purpose, use cases, alternatives, parameter constraints, and output format. The only real gap is the absence of a return-structure definition or error conditions, but 'cleaned rows' plus response_format gives enough for a competent agent to call it correctly.

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%, so the input schema already documents every parameter clearly, including examples for query. The Args section in the description mostly restates the schema without adding new semantics, so the baseline of 3 is appropriate.

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 and resource: 'Return actual cleaned rows of the dataset, with labels rather than codes.' It also names concrete use cases (reading open-ended answers, sanity-checking, inspecting records) and explicitly distinguishes itself from kobo_analyze/kobo_crosstab.

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 explicit when-to-use guidance ('read open-ended answers, sanity-check the data before drawing conclusions, or inspect specific records') and when-not-to-use guidance ('For aggregate figures prefer kobo_analyze or kobo_crosstab'). This leaves little ambiguity about tool selection.

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