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canvas_get_gradebook

Fetch a full course gradebook as a student-by-assignment table in one call to find missing work, spot failed assignments, and summarize class standing.

Instructions

Get the whole gradebook as one student-by-assignment table.

One call instead of N calls to canvas_list_submissions. Use it to find missing work, spot an assignment nobody passed, or summarise standing before office hours. FERPA: this is the full class record.

Args: course_id: numeric course id; defaults to CANVAS_DEFAULT_COURSE_ID. assignment_ids: comma-separated ids to restrict to; empty for all. include_names: label rows with student names as well as ids. max_chars: bound on the returned payload (0 = the server default).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_idNo
max_charsNo
include_namesNo
assignment_idsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden and does reasonably well: it flags the FERPA sensitivity of returning a full class record, discloses that max_chars bounds the payload, and explains the single-call performance trade-off. It does not explicitly state the operation is read-only or note any auth/permission prerequisites.

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?

Front-loads the core purpose in one sentence, follows with usage triggers and the FERPA warning, then an Args block. Every sentence adds information and nothing is padded.

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?

An output schema exists, so return values need not be described, and the description covers usage, parameters, and sensitivity. The remaining gap is the lack of any explicit read-only/permission statement for a tool that returns an entire class record.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet the Args block documents all four parameters with real semantics: course_id is numeric and falls back to CANVAS_DEFAULT_COURSE_ID, assignment_ids is comma-separated with empty meaning all, include_names controls row labels, and max_chars is a payload bound where 0 means the server default.

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?

States a specific verb and resource ('Get the whole gradebook') and defines the return shape as a student-by-assignment table. It explicitly distinguishes itself from canvas_list_submissions by framing itself as one call instead of N, so an agent can route without opening either schema.

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

Usage Guidelines4/5

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

Gives concrete when-to-use triggers (find missing work, spot an assignment nobody passed, summarise standing before office hours) and names the alternative (canvas_list_submissions) it replaces. It stops short of stating when the per-submission tool is still preferable, e.g. for a single assignment.

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