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Apply a previously previewed roster import

classdojo_apply_roster_import

Apply a previewed roster import to ClassDojo after explicit confirmation, then verify each class by reading it back to ensure accurate enrollment.

Instructions

Sends student names to ClassDojo only after explicit confirmation, then verifies each class by reading it back.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmYes
previewIdYes
Behavior4/5

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

Annotations already indicate this is a non-read-only, non-idempotent, non-destructive operation. The description adds valuable behavioral context by stating the confirmation requirement (aligning with the `confirm` parameter's const true) and the verification step after sending. It does not contradict annotations and supplements them with the two-step behavior, though it omits details about failure handling or side effects.

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

Conciseness5/5

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

A single, dense sentence that front-loads the core action, embeds the precondition, and ends with the verification step. There is no wasted text; every clause adds necessary information. The structure is efficient and proportionate to the tool's complexity.

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

Completeness3/5

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

For a write tool with no output schema and only two parameters, the description covers the primary behavior and precondition. However, it lacks details on what happens if verification fails, whether the operation is repeatable (idempotency is already annotated but not explained), and any side effects or error conditions. Given the stakes of sending data to an external service, additional context on failure handling would improve 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?

With 0% schema description coverage, the description must explain parameter purpose. It does clarify `confirm` as 'explicit confirmation' and `previewId` as referring to a 'previously previewed' import, but it does not explicitly state that `previewId` comes from the preview tool or describe its format beyond the schema. The description adds meaning but could be more explicit about the source of the previewId.

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

Purpose5/5

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

The description clearly states the tool's action: 'Sends student names to ClassDojo' (applies an import) and includes a distinguishing behavior: 'only after explicit confirmation, then verifies each class by reading it back.' This differentiates it from preview_roster_import (which only previews) and verify_roster_against_workbook (which compares to workbook, not ClassDojo). The verb-resource pairing is specific and unambiguous.

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

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly conditions usage on 'explicit confirmation' and a 'previously previewed' import, making it clear this is the apply step after a preview. However, it does not explicitly name alternatives or state when not to use it, though the sibling set and title imply the workflow. This is clear context but lacks direct exclusions or comparative 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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