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mess_reset_qr_token

Generate a new QR code token for IIIT Hyderabad Mess System authentication when the current token is lost, expired, or compromised.

Instructions

Reset the user's QR code token (shown at the mess counter).

Args: params: auth_key or session

Returns: JSON { token: string } — new URL-safe base64 token

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 indicate this is a non-readOnly, non-destructive, non-idempotent, openWorld operation. The description adds that it resets the token (implying mutation) and returns a new token, which aligns with annotations. However, it doesn't disclose behavioral traits like rate limits, authentication requirements beyond the params, or whether this invalidates previous tokens. With annotations covering basic hints, the description adds some context but lacks depth.

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 front-loaded with the purpose, followed by structured 'Args' and 'Returns' sections. It's appropriately sized with no wasted sentences, though the 'Args' section could be more integrated into the flow. The structure aids readability but isn't perfectly seamless.

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 moderate complexity (authentication mutation), annotations provide basic hints, and an output schema exists (implied by the Returns section). The description covers purpose, parameters, and return values adequately. However, it lacks context on error cases or side effects, which could be useful for completeness.

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%, but the description includes an 'Args' section explaining that 'params' requires 'auth_key or session', which adds meaning beyond the schema's technical definitions. However, it doesn't detail the semantics of these parameters (e.g., when to use one over the other) or other nuances. With 1 parameter and partial compensation, this meets the baseline.

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 action ('Reset') and the resource ('user's QR code token'), with additional context about where it's shown ('at the mess counter'). It distinguishes this tool from siblings like mess_get_info or mess_get_me by focusing on token resetting rather than retrieval. However, it doesn't explicitly differentiate from all siblings (e.g., mess_create_auth_key also deals with authentication).

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., needing authentication first), when resetting is appropriate (e.g., token compromise), or what happens to the old token. The sibling list includes many authentication-related tools (e.g., mess_create_auth_key, mess_login_msit), but no comparison is made.

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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