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send_peer_review_followup_campaign

Analyze peer review completion, preview recipient segmentation, then send urgent or gentle follow-up reminders after confirmation.

Instructions

Complete workflow: analyze peer reviews and send targeted reminders.

Two-step by design. Call it without a confirmation_token to get the analytics plus a preview of who would receive urgent vs gentle reminders and a token; show that to the educator, then call again with the token to actually send. The token is void if the completion analytics shifted in between.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assignment_idYesCanvas assignment ID
course_identifierYesCourse code or Canvas ID
confirmation_tokenNoToken from the preview call; omit to preview

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Beyond the annotations (idempotentHint false, destructiveHint false), the description discloses the two-step side-effectual behavior, the token invalidation if analytics shift, and that it sends urgent vs gentle reminders. This adds essential context for an agent to understand the non-idempotent nature and the safety of the preview call.

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?

Four sentences, purpose-first, with no filler. Every sentence contributes: purpose, design, invocation steps, and token caveat.

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

Completeness5/5

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

For a two-step workflow tool, the description fully explains the invocation sequence, the two modes, and the safety condition. The output schema covers return values, so no further description needed.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds critical semantics for confirmation_token: it comes from the preview call, is omitted to preview, and becomes void if analytics shifted. This contextualizes the parameters within the workflow.

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 'analyze peer reviews and send targeted reminders' and highlights the two-step workflow, distinguishing it from sibling tools like send_peer_review_reminders by explicitly explaining the preview-then-send design.

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 explains when to use it: call without confirmation_token for preview, show to educator, call again with token to send. It doesn't name alternatives but provides explicit step-by-step usage, making it clear when to invoke.

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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