Skip to main content
Glama

Update Assignment

update_assignment
DestructiveIdempotent

Update existing Canvas assignments by changing name, due date, description, points, submission types, or assignment group. Modify assignment details directly.

Instructions

Update an existing assignment in a course.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoNew assignment name
due_atNoNew due date in ISO 8601 format (e.g. 2026-05-01T23:59:00Z)
course_idYesThe Canvas course ID
descriptionNoNew assignment description (HTML supported)
assignment_idYesThe Canvas assignment ID
points_possibleNoNew maximum points
submission_typesNoNew allowed submission types
assignment_group_idNoNew assignment group ID
Behavior3/5

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

Annotations already declare destructiveHint=true and idempotentHint=true, which provide safety context. The description adds 'existing assignment', indicating it modifies present records. However, it does not disclose partial update semantics (e.g., only provided fields are changed), error handling, or permission requirements, so added value beyond annotations is minimal but not misleading.

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 a single, front-loaded sentence ('Update an existing assignment in a course.') with zero wasted words. It is highly concise and immediately understandable.

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

Completeness3/5

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

For a simple update tool with detailed schema annotations, the description is adequate but not comprehensive. It lacks guidance on return values or update behavior, but the schema covers parameters and annotations cover safety. The overall context is sufficient for an agent to correctly invoke the tool, but there is room for improvement in usage guidance.

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?

Schema description coverage is 100% for all 8 parameters, so the baseline is 3. The tool description adds no additional parameter-level context; it relies entirely on the schema's field descriptions. This is acceptable given the high schema coverage.

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 uses a specific verb ('update') and resource ('existing assignment in a course'), clearly distinguishing it from sibling tools like create_assignment, delete_assignment, and get_assignment. The phrase 'existing assignment' clarifies that it modifies an already-created assignment.

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 when to use the tool (when you have an existing assignment to modify), but it does not explicitly state when to prefer it over create_assignment or delete_assignment, nor does it mention alternatives or exclusions. The usage context is clear but not elaborated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/bruchris/canvas-lms-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server