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mess_get_feedback_window

Read-onlyIdempotent

Retrieve the time window in seconds available for submitting feedback after a meal in the IIITH Mess System.

Instructions

Get the feedback window time in seconds (time after a meal to submit feedback).

Args: params: auth_key or session

Returns: JSON integer (seconds)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds that it returns 'JSON integer (seconds)', which provides output format context not in annotations. However, it doesn't disclose rate limits, error conditions, or authentication behavior beyond what's implied by parameters. No contradiction with annotations exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and concise, with three clear sections: purpose, arguments, and returns. Each sentence adds value without redundancy. However, the 'Args' and 'Returns' sections could be integrated more smoothly, and there's minor verbosity in repeating 'params'.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (1 parameter, no nested objects) and rich annotations, the description is reasonably complete. It explains the purpose, parameters, and return value. The output schema exists, so the description doesn't need to detail return values further. However, it lacks context on authentication flow or error handling, which could be useful for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It states 'Args: params: auth_key or session', which clarifies that 'params' accepts authentication credentials. This adds meaning beyond the schema's property names. However, it doesn't explain the relationship between auth_key and session (e.g., if one is required, or if they're alternatives), leaving some ambiguity. With 0% coverage, this partial compensation warrants a baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get the feedback window time in seconds (time after a meal to submit feedback).' It specifies the verb 'Get' and the resource 'feedback window time', making it clear what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'mess_get_cancellation_window' or 'mess_get_skip_window', which have similar naming patterns but different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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., authentication requirements), timing considerations (e.g., when the feedback window applies), or related tools like 'mess_provide_feedback'. The only contextual clue is the parameter description, but this isn't explicit usage guidance.

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

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