sheets_get_data_validation

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds substantial behavioral context: it returns a 'compact list of unique validation rules grouped by their cell ranges (run-length encoded)' and enumerates the validation categories it can detect. This goes beyond the annotations by explaining the return format and grouping logic, making the tool's behavior transparent. It doesn't cover error cases or pagination, but for a read-only tool this is sufficient.

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 two sentences long, front-loaded with the core purpose, then the return format, then the use cases. Every sentence adds distinct value: the first states what it does, the second explains output structure and applicability. There is no redundancy or filler, so it earns a perfect score for efficiency.

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 moderate complexity (3 params, no output schema), the description adequately explains what the tool returns (compact list, run-length encoded, grouped by ranges) and why it's useful. It names the validation types it detects, providing a clear mental model. It doesn't provide an example output structure or edge cases, but for a read-only tool with stable annotations and a clear return description, this is complete enough for an agent to select and invoke correctly. Sibling tools don't overlap, so no context is missing.

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%, with each parameter (range, sheetName, spreadsheetId) clearly described in the schema. The description adds no extra parameter semantics beyond what the schema provides; it mentions 'sheet or range' but doesn't elaborate on parameter syntax or constraints. Since the schema already does the heavy lifting, a baseline score 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 uses a specific verb 'Read' with a clear resource 'data validation rules' and scope 'from a sheet or range.' It distinguishes itself from sibling tools by naming specific validation types (checkboxes, dropdown lists), which no other sibling tool covers. This makes the tool's unique purpose immediately obvious.

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?

The description explicitly states it is 'Useful for discovering checkboxes (BOOLEAN), dropdown lists (ONE_OF_LIST / ONE_OF_RANGE), number constraints, and custom formula validations,' providing clear context for when to use. It doesn't explicitly state when not to use it or name alternatives, but the use cases are concrete enough to guide selection. No exclusions are mentioned, so this is a clear context without full alternatives.

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