Lists course assignments with counts of submissions needing grading, optionally filtered to only those requiring grading.
Assignments in a course, with how many submissions still need grading.
| Name | Required | Description | Default |
|---|---|---|---|
| course_id | Yes | ||
| only_needing_grading | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.3.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It mentions an aggregated output detail (how many submissions still need grading) but omits whether the operation is read-only, permission needs, pagination, or any constraints; the output schema likely covers return values, so this addition is marginal.
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?
A single, front-loaded sentence fragment with no wasted words. It is appropriately sized for a simple list tool, though the fragment form is slightly less clear than a full verb phrase.
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?
An output schema exists, so return values need not be explained. The description states the resource and an output dimension, which is the minimum for a simple list tool, but it leaves parameter semantics and usage context uncovered.
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 description coverage is 0%, so the description must compensate for both parameters. It only implies course scoping via 'in a course' and never explains the only_needing_grading filter, adding little meaning beyond the self-descriptive parameter names.
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 identifies the resource (assignments in a course) and a distinguishing output detail (submission grading counts), clearly separating it from sibling tools like get_assignment and list_submissions. It lacks an explicit verb, but the name supplies 'list' and the scope 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 states what the tool returns but gives no explicit context for when to choose it over alternatives like get_assignment or list_submissions. Usage is only implied by the resource name, with no exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.