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Create Grading Standard

create_grading_standard
Destructive

Create a letter-to-percentage grading scheme in a course or account. Supply a title and scheme entries with lower-bound values to receive a standard ID for applying to a course.

Instructions

Create a new grading standard (letter-to-percentage scheme) in a course or account context. Provide either course_id or account_id (account requires admin). scheme_entries is an array of { name, value } objects where value is the lower-bound percentage as a fraction 0–1 (e.g. { name: "A", value: 0.94 } means A ≥ 94%). Entries will be sorted descending by value before sending to Canvas. Canvas POST body key is grading_scheme_entry (singular); the returned object uses grading_scheme (plural). Returns the created grading standard object including its id — use that id with apply_grading_standard_to_course to activate it on a course.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesDisplay name for this grading standard (e.g. "GPA 4.0 Scale")
course_idNoCourse ID to create the standard in (mutually exclusive with account_id)
account_idNoAccount ID to create the standard in (requires admin; mutually exclusive with course_id)
scheme_entriesYesGrading scheme entries. Each entry: { name: string, value: number (0–1) }. The lowest grade should have value 0.0.
Behavior2/5

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

Annotations include destructiveHint: true but the description doesn't elaborate on the destructive aspect beyond implying creation. It does mention the POST key and response key difference, which is useful. However, it doesn't state side effects like whether it replaces an existing standard or if there are limitations. Given the annotation, some credit for adding request/response key nuance, but no behavioral details about side effects or irreversibility.

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?

Single paragraph, information-dense, front-loaded with purpose, then context, then parameter semantics, then return usage. No fluff, every sentence provides unique value.

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?

Given the tool complexity (4 params, one nested object), the description covers purpose, input requirements, sorting, API key naming nuance, and how to use the returned id. It's missing some details like whether the returned object format is fully described (no output schema), but it gives enough to proceed. With annotations (openWorldHint, destructiveHint) and 100% schema coverage, it's reasonably complete.

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

Parameters4/5

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

Schema coverage is 100% (all parameters have descriptions), but the description adds value: explains the value fraction meaning, sorting behavior, and the lower-bound concept. This goes beyond schema text (e.g., schema doesn't mention sorting or that lowest grade should be 0.0). Since coverage is high, baseline is 3, and this adds significant extra meaning, so 4 is justified.

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?

Clearly states 'Create a new grading standard' with specific context (course/account), and the description adds important details like the scheme_entries format and sorting behavior, distinguishing this from sibling tools like list_grading_standards or apply_grading_standard_to_course.

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 explains when to use it (create) and how it relates to activation ('use that id with apply_grading_standard_to_course'), plus clarifies the mutually exclusive course_id/account_id choice and admin requirement for accounts.

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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