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canvas_assignment

Read-onlyIdempotent

Retrieve a Canvas assignment's full details, including description, rubric, due dates, and your submission status, by providing course and assignment IDs.

Instructions

Read one assignment in full: description, rubric, dates and your submission status.

Input Schema

NameRequiredDescriptionDefault
rawNotrue: Canvas's unmodified JSON (UTC times, HTML).
course_idYesCanvas course id, from canvas_courses.
assignment_idYesAssignment id, from canvas_assignments or a module item.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so the safety profile needs no restating. The description adds real context by disclosing that results include the caller's own submission status (user-scoped) and that content is returned "in full," but says nothing about whether output is normalized or raw HTML/UTC, which the schema's `raw` flag suggests is a meaningful behavioral fork.

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?

One sentence, front-loaded with the verb and scope, and every clause (description, rubric, dates, submission status) tells the agent something concrete about payload. No filler.

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

Completeness4/5

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

For a simple single-fetch read with full annotation and schema coverage, the enumeration of returned fields substitutes adequately for a missing output schema. The only residual gap is not stating whether dates/HTML are normalized by default versus when `raw` is true, which the agent must infer.

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% and all three parameters carry documentation, including the provenance of course_id/assignment_id and the raw JSON vs. normalized tradeoff. The description adds no param-level meaning beyond the schema, so the baseline 3 applies.

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?

Specific verb ("Read") plus a single-resource target ("one assignment") and an explicit enumeration of what comes back (description, rubric, dates, submission status). The singular framing implicitly separates it from the list-oriented sibling canvas_assignments, but no sibling is named outright.

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?

Usage is only implied by "Read one assignment in full" — an agent can infer this is the detail-fetch after canvas_assignments, but there is no explicit when-to-use, no stated alternative for bare submission data (e.g. canvas_submission), and no prerequisite notes.

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