grade_submissionPost or update a grade for a student's submission in Canvas. Provide course, assignment, user, and grade to apply the score.
Post or update a grade for a submission. Requires grading permissions.
| Name | Required | Description | Default |
|---|---|---|---|
| grade | Yes | The grade to assign (e.g. "95", "A", "pass") | |
| user_id | Yes | The Canvas user ID | |
| course_id | Yes | The Canvas course ID | |
| assignment_id | Yes | The Canvas assignment ID |
Changes observed during successful MCP inspections.
v1.18.11Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"v1.18.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true and idempotentHint=true, so the description does not need to restate those. It adds the permission requirement and 'post or update' semantics, but it does not disclose grade history effects, whether existing grades are overwritten, or other consequences. Given annotation coverage, this is adequate but not rich.
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?
The description is two short sentences with no filler. The verb and resource are front-loaded, and the permission note is the only extra context, making it appropriately concise.
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 mutation with fully documented parameters and annotations covering side effects, this is minimally sufficient. However, there is no output schema and the description does not explain what the tool returns or how grade strings are interpreted, leaving some gaps in a no-output-schema context.
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?
The input schema documents all four parameters with descriptions (100% coverage), so the baseline is 3. The description adds no additional meaning to the parameters, relying entirely on the schema.
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?
The description states a specific verb ('Post or update') and a clear resource ('a grade for a submission'), so the agent knows what the tool does. It does not explicitly differentiate from sibling grading tools like submit_rubric_assessment or score_quiz_question, but the core purpose is unambiguous.
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?
The description provides a prerequisite ('Requires grading permissions') but gives no guidance on when to use this tool instead of alternatives such as comment_on_submission, submit_rubric_assessment, or project_grade. The agent is left to infer the correct context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.