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

The description adds real context beyond the annotations: the suggest-then-save workflow, that dry_run defaults to true and reports pending studies and blockers, that false actually launches, and that extraction is paid and gated on full-text approval. However, with destructiveHint=true set, it never states what is overwritten by define_columns or consumed by a real run, nor whether a launch can be cancelled or reverted.

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?

Front-loaded with the trigger condition, then a compact per-action list; nearly every clause carries information. The telegraphic fragments ('AI extraction; dry_run defaults to true') read tersely but remain parseable, with only mild redundancy against the schema's dry_run description.

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 5-parameter mutating tool with no output schema, it covers the essentials an agent needs before calling: action semantics, dry-run default, cost/approval gating and the order of operations. Remaining gaps are the shape of the run response and what governs quota consumption, which matter but are secondary to 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 coverage is 80%, so the schema already documents dry_run, project_id and idempotency_key. The description still adds meaning the schema lacks: which action consumes `columns`, that suggest_columns output is discarded, and what dry_run=true actually reports (pending studies, blockers). The idempotency_key is left entirely to the schema.

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 concrete resource (data extraction) and breaks the tool into three specific actions (suggest_columns, define_columns, run), each with a one-line meaning. It never mentions the sibling revisia_extraction (likely the read/status counterpart), so an agent must infer the act/read split from naming convention alone.

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?

Opens with an explicit trigger ('Use this when preparing data extraction') and gives per-action distinctions, notably that suggest_columns results are not saved while define_columns persists accepted columns. It also states prerequisites (paid feature, approved full-text stage). It stops short of saying when NOT to use it or naming revisia_extraction as the alternative for reading existing definitions.

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