validate_tool_output

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

Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds that it is read-only, never blocks, uses two-layer validation with deterministic rules and AI review, both layers must agree before feedback is filed, and it auto-files feedback. This provides comprehensive behavioral context without contradicting annotations.

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 detailed but well-structured: purpose first, then parameter details, then output and usage guidance. It is front-loaded and efficient, though slightly verbose. Every sentence adds value, with no fluff.

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 tool's complexity (two-layer validation, feedback integration), the description covers the workflow, return values (pass/issues_found, layers, feedback status), and error handling via report_feedback. It is complete and provides all necessary context for an agent to use the tool correctly.

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 100% with descriptions for all three parameters. The description enriches these by explaining where to find the tool_id and query_hash (e.g., 'Find in the tool_id field of any response'), and clarifies that response_json should be the full serialised response. This adds usability context beyond 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 clearly states the tool validates DataNexus tool responses for data quality issues using two-layer validation. It specifies the verb 'validate' and the resource 'DataNexus tool response', and distinguishes itself from siblings like 'report_feedback' by contrasting automated validation vs manual reporting.

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?

Explicitly states when to use this tool ('Use validate_tool_output to check data quality') and when to use the alternative 'report_feedback' for manual reporting or when the tool's response doesn't serve the user's need. Also provides detailed instructions for handling gaps via feedback.

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