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Glama

list_submissions

Retrieve student submissions for a coursework, filtering by submission state, student, or page size to track turned-in, returned, or new work.

Instructions

List student submissions for a coursework (status: TURNED_IN, RETURNED, NEW, late status, assigned grade).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statesNoFilter by submission states: NEW, CREATED, TURNED_IN, RETURNED, RECLAIMED_BY_STUDENT.
userIdNoOptional student filter ('me' for current user, or student user ID).
courseIdYesThe unique identifier of the course.
pageSizeNoMaximum number of submissions to return.
courseWorkIdYesThe coursework identifier (or '-' for all coursework in the course).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

There are no annotations, so the description carries the full behavioral burden. It conveys a read-only listing operation and indicates the kind of data returned, but it does not disclose pagination behavior, ordering, response limits, or whether any side effects occur. The verb 'List' implies read-only, which helps, but the description could be more explicit.

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 concise and front-loaded: one sentence states the main operation, with a short parenthetical about returned information. It contains no filler, though the parenthetical could be structured more clearly by separating states from return fields.

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?

With no output schema and no annotations, the description should compensate by explaining return shape, pagination, and exclusions. It only partially mentions returned fields and gives no usage routing or behavioral details, so an agent is under-informed for a five-parameter list tool.

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 schema has 100% description coverage, so the schema already documents all five parameters. The description adds little parameter-level meaning beyond the schema; the statuses mentioned in the description are already represented by the states parameter and the course/coursework IDs are already documented in the schema.

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 clearly states a specific action and resource: 'List student submissions for a coursework.' It also hints at returned data (statuses, late status, assigned grade) and is distinguishable from the sibling get_submission by the list-vs-single-operation semantics. The parenthetical is slightly imprecise because it mixes submission states with return fields, but the core purpose remains clear.

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?

No when-to-use guidance is provided, and no alternatives are mentioned. The description does not explain when to prefer this over get_submission or how it relates to turn_in_assignment/reclaim_assignement, leaving the agent to infer the intended use case from the tool name alone.

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