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Explain Grading Policy

explain_grading_policy
Read-only

Explains the grading automation rules configured for a Canvas course: - Missing-submission policy: whether blank/unsubmitted work is automatically scored 0 (or another deduction), or left unpenalised.

Instructions

Explains the grading automation rules configured for a Canvas course:

  • Missing-submission policy: whether blank/unsubmitted work is automatically scored 0 (or another deduction), or left unpenalised.

  • Late-submission policy: whether Canvas applies a per-day or per-hour percentage deduction to late submissions, and whether there is a floor below which the grade cannot fall.

  • Assignment-group weighting: whether the course uses weighted groups, and the weight of each group.

  • Grading scheme: whether a letter-grade scheme (A/B/C/F mapping) is applied to the final score.

Also returns a plain-language summary paragraph you can share with students or instructors.

Note: the late/missing policy section requires instructor or admin permissions. Students receive the group-weighting and grading-scheme sections only, with a caveat noting what is unavailable. Use explain_grade to compute the actual weighted grade for a specific student.

Input Schema

NameRequiredDescriptionDefault
course_idYesCanvas course ID to explain the grading policy for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.18.15
    • addedInput schema / properties / course_id / anyOf
      Added value: +[
+  {
+    "exclusiveMinimum": 0,
+    "maximum": 9007199254740991,
+    "type": "integer"
+  },
+  {
+    "pattern": "^[1-9][0-9]{0,18}$",
+    "type": "string"
+  }
+]
    • removedInput schema / properties / course_id / exclusiveMinimum
      Removed value: -0
    • removedInput schema / properties / course_id / maximum
      Removed value: -9007199254740991
    • removedInput schema / properties / course_id / type
      Removed value: -"integer"
  2. Changed1 schema field changedv1.18.11
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. Addedv1.18.3

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and destructiveHint, but the description adds substantial context beyond them: the late/missing section requires instructor or admin permissions, students receive only two sections plus a caveat, and a shareable plain-language summary is produced. These auth and data-visibility behaviors are not derivable from annotations or schema.

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?

Front-loaded with the purpose, then a bulleted breakdown of returned sections that each earn their place by clarifying scope. Slightly long, but the structure is scannable and no sentence is filler.

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

Completeness5/5

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

With no output schema, the description carries the return-value burden and does so thoroughly by listing all returned sections plus the summary paragraph. Permission caveats and the sibling routing close the remaining gaps an agent would need.

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?

Only one parameter (course_id) with 100% schema description coverage, so the schema already documents it fully. The description adds no format or type detail beyond what the schema provides, making the baseline 3 appropriate.

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 (explains) and resource (grading automation rules) and enumerates the exact facets returned (missing-submission, late-submission, weighting, scheme). It distinguishes itself from the sibling explain_grade by naming it as the compute-oriented alternative.

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

Usage Guidelines5/5

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

Explicitly routes the agent: use explain_grade to compute an actual weighted grade for a specific student, implying this tool is for understanding policy instead. It also states the permission-conditioned access model (instructor/admin vs student), giving clear context for when the tool will return partial data.

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

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