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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It implies a write operation ('Report'), but doesn't specify whether this is a mutation, if it requires authentication, what happens after submission (e.g., confirmation, error handling), or any rate limits. For a tool that likely modifies data, this is a significant gap in transparency.

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, efficient sentence: 'Report data quality issues for a business.' It is front-loaded with the core purpose and wastes no words, making it highly concise and well-structured.

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 complexity (a mutation tool for reporting issues), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, response format, or error conditions. For a tool that likely impacts data quality, more context is needed to guide the agent effectively.

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 the schema already documents all parameters (business_id, type, comment) with descriptions and enum values for 'type.' The description adds no additional meaning beyond the schema, such as explaining the business_id format or when to use each feedback type. Baseline 3 is appropriate as the schema does the heavy lifting.

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: 'Report data quality issues for a business.' It specifies the verb 'Report' and the resource 'data quality issues for a business,' making it distinct from siblings like get_business or search_businesses. However, it doesn't explicitly differentiate from all siblings (e.g., suggest might be related), so it falls short of a perfect score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a business ID), exclusions, or comparisons to siblings like get_business (which might retrieve data) or suggest (which might propose changes). This lack of context leaves the agent to infer usage.

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