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send_conversation

Send messages to students via Canvas conversations. Specify course, recipients, subject, and body for group or individual messaging.

Instructions

    Send messages to students via Canvas conversations.

    Args:
        course_identifier: Course code or Canvas ID
        recipient_ids: List of Canvas user IDs
        subject: Message subject (max 255 chars)
        body: Message content
        group_conversation: Create group conversation (required for custom subjects)
        bulk_message: Send individual messages with same subject to each recipient
        context_code: Course context (e.g., "course_60366")
        mode: "sync" or "async" (use async for >100 recipients)
        force_new: Force new conversation even if one exists
        attachment_ids: Optional attachment IDs
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_identifierYes
recipient_idsYes
subjectYes
bodyYes
group_conversationNo
bulk_messageNo
context_codeNo
modeNosync
force_newNo
attachment_idsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description must carry all behavioral disclosure. It mentions parameters like 'force_new' which hints at behavior, but fails to describe side effects, authentication needs, or error responses. The existence of an output schema partially mitigates this, but the description itself 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 concise with a clear summary sentence followed by a parameter list. It avoids redundancy but could be more structured (e.g., using bullet points). Every sentence adds value, and it's appropriately sized for the complexity.

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 complexity (10 parameters, 4 required) and no annotations, the description covers key edge cases like bulk messaging and async mode. It references an output schema, so return values need not be detailed. However, it omits permissions or rate limits, which are relevant for a messaging tool.

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 description coverage is 0%, so the description must explain parameters. It adds meaning for many, e.g., 'group_conversation: Create group conversation (required for custom subjects)' and 'mode: sync or async (use async for >100 recipients)'. Some parameters like 'course_identifier' lack format details, but overall it adds significant value.

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 'Send messages to students via Canvas conversations' with specific verb and resource. It distinguishes from sibling tools like 'list_conversations' or 'mark_conversations_read' by focusing on sending new messages. The parameter list further clarifies the action.

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

Usage Guidelines3/5

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

Internal usage guidelines are provided, e.g., 'use async for >100 recipients' and 'group_conversation required for custom subjects'. However, it does not compare with sibling tools like 'send_bulk_messages_from_list', leaving the choice between them ambiguous.

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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