validate_result

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

Annotations already indicate safe read-only behavior. The description adds value by explaining that the tool re-executes the SQL, extracts numbers and terms, and checks them against data. This covers the key behavioral aspects without contradiction.

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 concise (around 60 words) and well-structured: an introductory sentence defining the tool's purpose, a usage recommendation, and a brief note on the execution process, followed by a clear parameter list. Every sentence adds value with no 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?

The tool has an output schema (not shown), so the description does not need to detail return values. However, it does not mention what the output looks like (e.g., boolean, match report), which would be helpful for an agent to interpret results. Also lacks any mention of error conditions or limitations, leaving minor gaps in completeness.

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?

The input schema has no descriptions (0% coverage), but the description provides full semantics for both required parameters: 'sql' is explained as 'the SQL query that produced the data backing the claim' and 'claim' as 'the natural-language claim to verify.' This completely compensates for the missing schema 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 clearly states the tool's purpose: 'Validate that a claim is supported by query results.' It specifies the action (validate) and the resource (claim), and distinguishes it from sibling tools like sql_query or compare_datasets by describing the verification process.

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 provides explicit guidance: 'Call this after making a data claim to verify it against the source.' This clearly indicates when to use the tool, though it does not explicitly state when not to use it or mention alternatives beyond the context of sibling tools.

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