validate_tool_output

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

Discloses read-only, never blocks behavior, two-layer validation process, and auto-filing conditions. Lacks detail on error responses but covers core behavioral traits sufficiently.

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?

Description is thorough but slightly verbose. Still front-loaded with core purpose and well-organized into sections, making it efficient for an agent to parse.

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?

Covers purpose, parameters, behavior, and usage guidance. With output schema present, high-level return description suffices. No major gaps given 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?

With 0% schema description coverage, description fully explains all three parameters: tool_id (with examples), query_hash (purpose), response_json (format). Adds context beyond bare 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?

Clearly states it validates DataNexus tool response for data quality using two-layer validation. Distinguishes from sibling report_feedback by explicitly contrasting use cases.

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 says when to use this tool versus report_feedback. Provides fallback instruction if tool output is insufficient, reinforcing when to leverage alternatives.

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