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

Annotations declare destructiveHint=true, and the description meaningfully scopes that destructiveness: removed rows leave the training data while the uploaded file is kept and nothing else is deleted. This is exactly the kind of clarifying context that goes beyond a bare destructive flag. It does not mention permissions or reversibility, so not a 5.

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?

Three tight sentences, with the ordered operation list and the 'only what the user chose' constraint front-loaded, and the destructive-scope clarification last. No filler, though the sentence slightly repeats the ordering idea.

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 destructive, nested-object mutation tool with no output schema and sparse parameter descriptions, the definition covers the operation order, the skip-if-not-chosen rule, and the deletion scope adequately. Prerequisite/permission context and per-field semantics remain unstated but are not strictly required for correct invocation.

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 only 20% (just model_id), so the description must compensate, and it does by mapping the operations to the parameters in execution order: merge category names, leave categories out, remove near-duplicates, and mask/remove/keep personal information. This adds real meaning over the bare nested schema, though it doesn't document field-level details like the 'into'/'labels' sub-structure.

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 names a specific verb and resource ('Apply the user's choices to the training data') and enumerates the four concrete operations it performs, so an agent knows exactly what the tool does. It stops short of explicitly distinguishing itself from near-siblings like data_quality or correct_labels, keeping it at a 4.

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?

'Only what the user chose' implies the precondition that the user has already made quality selections and that unspecified operations are skipped, which is useful implied guidance. There is no explicit when-to-use/when-not statement and no named alternative tool, so it remains implied rather than directive.

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