check_consistency

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

No annotations are provided, so the description carries the full burden. It states the check function and gives an example but does not disclose whether the operation is read-only, what output format to expect, or any side effects. This is a minimum viable disclosure for a check-like tool.

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 a single, focused sentence with no redundancy. It is well-structured, front-loaded with the core action, and contains no filler.

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?

For a tool with one parameter and no output schema, the description gives the core purpose but omits expected return values or error conditions. The schema handles the parameter, so the description is sufficient for basic use but not fully complete.

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 provides a complete description for entity_ids (100% coverage). The description adds context by explaining the purpose but does not add new parameter semantics beyond what the schema already provides.

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 'check' and clearly identifies the resource (logical entity attributes across systems) with a concrete example. It also differentiates from sibling tools like resolve_entity and fuzzy_match_records by focusing on consistency verification rather than resolution or matching.

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 implies the tool should be used when you need to verify data consistency across systems, but it does not explicitly mention when not to use it or name alternative tools like resolve_entity. The guidance is implicit rather than explicit.

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