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vishalsachdev

Canvas MCP Server

by vishalsachdev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Create Student Anonymization Map

create_student_anonymization_map
DestructiveIdempotent

Generates a local CSV mapping real student data to anonymous IDs for a Canvas course, so students can be referenced anonymously using the course code or Canvas ID.

Instructions

Create a local CSV file mapping real student data to anonymous IDs for a course.

Input Schema

NameRequiredDescriptionDefault
course_identifierYesCourse code or Canvas ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.10.0
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "type": "object",
-  "x-fastmcp-wrap-result": true
-}New value: +null
  2. Changed7 schema fields changedv1.8.0
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / course_identifier / description
      Added value: +"Course code or Canvas ID"
    • removedInput schema / properties / course_identifier / title
      Removed value: -"Course Identifier"
    • removedInput schema / title
      Removed value: -"create_student_anonymization_mapArguments"
    • removedOutput schema / properties / result / title
      Removed value: -"Result"
    • removedOutput schema / title
      Removed value: -"create_student_anonymization_mapOutput"
    • addedOutput schema / x-fastmcp-wrap-result
      Added value: +true
  3. Changed1 schema field changedv1.0.0
    • addedInput schema / title
      Added value: +"create_student_anonymization_mapArguments"
  4. First observed

TDQS

B3.3/5.0
Behavior3/5

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

The annotations declare destructiveHint=true and idempotentHint=true, so the description should clarify what is destroyed or overwritten. It does add useful privacy context by saying the CSV maps real student data, but it does not explain whether an existing map is overwritten, where the file is written, or how idempotency behaves.

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?

The definition is a single efficient sentence with zero waste. The core action and artifact are front-loaded.

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

Completeness3/5

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

For a one-parameter tool, the description covers the central purpose and privacy sensitivity. However, given destructiveHint=true and no output schema, it should say more about file location, overwrite behavior, and the relationship to get_anonymization_status.

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% for the single course_identifier parameter, and the schema already documents that it accepts a course code or Canvas ID. The description adds only that the mapping is for a course, which is already implied by the parameter.

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 states a specific verb and artifact: create a local CSV mapping real student data to anonymous IDs for a course. It is clear what the tool produces, though it does not explicitly distinguish itself from the sibling get_anonymization_status tool.

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?

The description gives no guidance on when to use this tool versus alternatives such as get_anonymization_status, nor does it mention prerequisites, sequencing, or exclusions. The intended workflow must be inferred.

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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