Bulk: Validate CSV (dry run)

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

With no annotations, the description discloses key behaviors: it makes no changes, reports specific validation results (row count, present/absent columns, unknown columns, missing required fields, duplicate keys), and notes pacing (~1 request/second). It could further detail error handling or return format, but overall transparency is strong.

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 three sentences, front-loaded with the main purpose and non-destructive guarantee. Every sentence provides essential information—scope, report contents, pacing, workflow, and input methods—with no filler or redundancy.

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 validation tool with no output schema and no annotations, the description compensates well by covering purpose, safety, report contents, pacing, and input alternatives. It does not detail interactions with operation, key_column, or address_config, but the schema already documents those, so the description is sufficiently complete for the tool's complexity.

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 86%, giving a baseline of 3. The description adds value by explaining the two CSV input alternatives ('csv_content (inline) or csv_path (a readable file path)') and connecting 'field configuration' to the fields parameter. This goes beyond the schema's individual field descriptions.

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 verb ('Validate'), resource ('bulk CSV'), and scope ('against a field configuration') with an explicit non-destructive emphasis ('WITHOUT making any changes'). It clearly distinguishes from sibling bulk_execute by describing validation as a dry run.

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?

Provides explicit workflow guidance: 'Always run this and review it before bulk_execute.' This names the primary alternative and gives a clear when-to-use rule. It also clarifies input methods (csv_content or csv_path).

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