get_outcomeRetrieve a single learning outcome with its full description and mastery scale using its outcome ID. Read-only lookup; get the ID from list_outcomes first.
Get one learning outcome with its description and mastery scale. Read-only. Use list_outcomes to find outcome IDs.
| Name | Required | Description | Default |
|---|---|---|---|
| outcome_id | Yes | Learning outcome ID (numeric string). Get it from list_outcomes. |
Changes observed during successful MCP inspections.
v1.0.2Input schema / properties / outcome_id / descriptionPrevious value: -"Canvas ID (numeric string)"New value: +"Learning outcome ID (numeric string). Get it from list_outcomes."v1.0.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint, so safety behavior is well covered. The description repeats 'Read-only' and adds useful return content ('description and mastery scale'), but does not go much beyond that, such as error behavior for invalid IDs. With annotations doing most of the behavioral work, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, front-loaded with the core action and return content. The read-only note is redundant with annotations but not enough to undermine otherwise efficient structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-resource read tool, the description covers purpose, return content, and ID source. Annotations supply the safety profile, and no output schema means the brief return mention is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the sole parameter is documented in the schema with type and source ('Get it from list_outcomes'). The description reinforces that source guidance but adds little syntax or format detail beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Get one learning outcome.' It also specifies the returned content ('description and mastery scale') and points to list_outcomes for ID discovery, distinguishing it from the list tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Clearly directs the agent to use list_outcomes to find outcome IDs, establishing the prerequisite for this tool. It does not explicitly state exclusions versus related tools like get_outcome_rollup or get_my_outcome_results, but the single-outcome purpose is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.