cross_reference_check

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

No annotations are provided, so the description carries full behavioral disclosure burden. It mentions outputs (consistency score and detailed comparison) which is helpful, but doesn't disclose any side effects, failure modes, data handling, or what happens on mismatch. For a data-comparison tool, details on normalization rules or error behavior would be valuable.

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?

Three concise sentences with no wasted words, and the output type is front-loaded. Slightly deeper behavioral context could be added, but the current length is efficient and appropriate.

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?

With no output schema and no annotations, the description should disclose more about return shape and side effects. It mentions 'consistency score and detailed comparison' which helps, but doesn't cover edge cases like empty reference arrays, handling of missing comparison fields, or the meaning of tolerance levels. Adequate but with notable gaps given the zero annotation coverage.

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%, so all 4 parameters are documented in the schema. The description adds nothing about parameter semantics beyond the schema. Baseline 3 applies since the schema does the heavy lifting and the description doesn't need to compensate.

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 compares data from multiple agents and detects discrepancies, with a specific verb (compare) and resource (data from agents). It returns a consistency score. However, it doesn't explicitly differentiate from siblings like detect_hallucination_markers or output_consistency_score, which could overlap in purpose, so it doesn't fully earn a 5.

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?

'Essential for multi-agent coordination' provides context on when to use it. However, there are no explicit exclusions or when-not-to-use guidance, and sibling tools like output_consistency_score likely overlap significantly in purpose, so the description fails to help the agent choose between them.

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