submit_feedback

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 mentions 'anonymous feedback' which hints at privacy, but fails to describe critical traits like whether submission is irreversible, if there are rate limits, authentication requirements, or what happens after submission (e.g., confirmation). For a mutation tool with zero annotation coverage, this is a significant gap.

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 that front-loads the core purpose without unnecessary words. Every part of the sentence ('submit anonymous feedback for a meal you've availed') directly contributes to understanding the tool's function, making it appropriately sized 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 tool's complexity (a mutation with 4 parameters) and lack of annotations and output schema, the description is incomplete. It does not address behavioral aspects like side effects, error conditions, or response format, leaving the agent with insufficient context to use the tool effectively beyond basic parameter input.

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 (meal_date, meal_type, rating, remarks) with details like format, enum values, and constraints. The description adds no additional meaning beyond what the schema provides, such as explaining how 'meal_date' relates to 'availed' meals or the impact of 'remarks'. Baseline 3 is appropriate when 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 action ('submit anonymous feedback') and the target resource ('for a meal you've availed'), which is specific and actionable. However, it does not explicitly distinguish this tool from sibling tools like 'get_meal_rating' or 'register_meal', which reduces clarity in a crowded toolset.

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 (e.g., 'get_meal_rating' for reading ratings, 'register_meal' for meal registration) or any prerequisites (e.g., must have availed the meal first). It lacks explicit when/when-not instructions or named alternatives.

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