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canvas_inbox_get

Retrieve a complete Canvas LMS conversation thread including all messages, timestamps, attachments, and participant details by providing the conversation ID.

Instructions

Get a specific conversation with all messages.

Returns:

  • Full conversation thread

  • All messages with timestamps

  • Attachments information

  • Participant details

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conversation_idYesThe conversation ID
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool returns a full conversation thread with messages, timestamps, attachments, and participant details, which adds useful behavioral context beyond just 'get'. However, it doesn't mention potential limitations like rate limits, authentication needs, or error conditions, which are important for a read operation.

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?

The description is well-structured and concise, with a clear purpose statement followed by a bulleted list of return details. Every sentence earns its place by providing essential information without redundancy, making it easy to scan and understand quickly.

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 output schema, no annotations), the description is fairly complete. It explains what the tool does and what it returns, which is sufficient for a simple read operation. However, without annotations or output schema, it could benefit from more behavioral details like error handling or data format specifics.

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?

The input schema has 100% description coverage, with the single parameter 'conversation_id' clearly documented. The description doesn't add any additional semantic information about the parameter beyond what the schema provides, so it meets the baseline of 3 where the schema does the heavy lifting.

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 with a specific verb ('Get') and resource ('a specific conversation with all messages'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from its sibling 'canvas_inbox_list', which might handle listing conversations rather than retrieving a specific one, though this distinction is implied.

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?

The description implies usage by specifying it retrieves 'a specific conversation', suggesting it should be used when you have a conversation ID. However, it lacks explicit guidance on when to use this versus alternatives like 'canvas_inbox_list' or other inbox-related tools, leaving some ambiguity for the agent.

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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