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risnake

@rishblob/canvas-mcp-server

by risnake

grade_submission

Grade a student submission in Canvas by providing course, assignment, and user IDs along with the grade value and an optional comment.

Instructions

Grade a student submission for a Canvas assignment

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gradeYesThe grade value (e.g. '95', 'A', 'pass', 'incomplete')
commentNoOptional text comment to include with the grade
user_idYesThe user/student ID
course_idYesThe course ID
assignment_idYesThe assignment ID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Grade' without revealing whether an existing grade is overwritten, whether the grade is posted to the student, what permissions are needed, or what the response contains. For a state-changing action, this is a significant gap.

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 a single, direct sentence with no filler or redundancy. It is concise and easily parsed, though the brevity leaves room for missing behavioral and usage context.

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

Completeness2/5

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

For a write operation with no annotations, no output schema, and no usage guidance, this description is incomplete. An agent would need to infer important context such as side effects, prerequisites, and what happens after grading. The schema fully documents parameters but does not compensate for the missing operational context.

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 for all five parameters, so the schema already explains course_id, assignment_id, user_id, grade, and comment. The description itself adds no additional parameter-level meaning, but because the schema is complete, the baseline of 3 is appropriate.

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 states a clear action ('Grade') on a specific resource ('a student submission for a Canvas assignment'), so an agent can understand the core purpose. It does not differentiate the tool from siblings like list_submissions or get_submission, but the verb and object make the intended operation fairly unambiguous.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives, and no prerequisites such as verifying the submission exists or the student is enrolled. Context of use must be inferred entirely from the tool name and schema.

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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