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vishalsachdev

Canvas MCP Server

by vishalsachdev
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fix_accessibility_issues

Apply automated fixes to resolve accessibility issues in Canvas course content. Preview changes with dry_run before applying corrections for missing table headers, low contrast text, and other problems.

Instructions

Auto-fix accessibility issues in Canvas course content.

    Applies automated fixes for issues flagged as auto_fixable by the scanner.
    Run scan_course_content_accessibility first to see what will be fixed.
    Default is dry_run=True (preview only). Set dry_run=False to apply changes.

    Args:
        course_identifier: Course code or Canvas ID
        fix_types: Comma-separated fix types to apply:
            th_scope - Add scope="col" to <th> without scope
            low_contrast - Fix white text on #ff5f05 orange backgrounds
            legacy_designplus - Migrate kl_ classes to dp- equivalents
            redundant_alt_prefix - Remove "image of" prefix from alt text
        content_types: Comma-separated types to fix: pages, assignments
        dry_run: If True, preview changes without applying. Set False to apply.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_identifierYes
fix_typesNoth_scope,low_contrast,legacy_designplus,redundant_alt_prefix
content_typesNopages
dry_runNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.5/5.0
Behavior4/5

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

Without annotations, the description carries full burden. It describes that fixes are applied for auto_fixable issues, and that dry_run controls preview vs. actual application. However, it lacks explicit mention of permanence of changes when dry_run=False or required permissions, though the dry_run safeguard mitigates risk.

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?

Well-structured with sections; front-loaded with purpose. Each sentence adds value. Could be slightly more concise, but overall efficient and clear.

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?

Given the tool's complexity (4 params, no annotations), the description covers purpose, usage, parameters, and behavioral aspects comprehensively. Output schema exists, so return value details are not required.

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 coverage is 0%, so description must explain parameters fully. It does so, detailing course_identifier, fix_types (with comma-separated examples), content_types, and dry_run with defaults. Provides meaningful context beyond schema titles and types.

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?

Description clearly states the tool auto-fixes accessibility issues in Canvas course content. It specifies the verb 'auto-fix' and resource 'accessibility issues', and distinguishes itself from siblings like scan_course_content_accessibility and format_accessibility_summary by describing its action and prerequisite.

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?

Explicitly instructs to run scan_course_content_accessibility first, and explains the dry_run parameter for safe preview. Provides clear context on when to use (after scanning) and how to apply changes, though it doesn't mention when not to use or alternatives.

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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