create_rubric_from_csv

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

Beyond the sparse annotations (idempotentHint=false, destructiveHint=false), the description richly discloses behavior: it uses Canvas's native CSV import endpoint, polls to terminal workflow_state, requires a Rubric Name column, and explicitly warns that imported rubrics land in Draft state (not visible to list_rubrics) and that succeeded_with_errors may mean zero rubrics were created. This greatly aids agent understanding of side effects and edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: a concise opening sentence states the core purpose, followed by a code block showing the exact CSV format and two clearly labeled behavioral caveats. Every sentence provides necessary information for correct use, without fluff or redundancy.

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

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

For a complex import tool with minimal annotations and an output schema not shown, the description covers the essential operational details: required parameters, CSV format, polling behavior, terminal states, and known pitfalls. It is thorough enough for an agent to invoke the tool correctly and interpret results.

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

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

Schema coverage is 100%, but the description adds substantial meaning for csv_content by specifying the required Rubric Name column and providing a full CSV format example. It also clarifies that multiple rubrics can be created by using distinct Rubric Name rows. This goes beyond the schema's basic parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Create one or more rubrics in a course from a CSV string.' It specifies the resource (rubrics), the action (create), and the method (from CSV), distinguishing it from sibling tools like create_rubric or list_rubrics.

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

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

The description does not explicitly state when to use this tool versus alternatives such as create_rubric. It implicitly conveys that CSV input is the use case, but there is no direct comparison or exclusion guidance. The behavioral notes (e.g., Draft state, succeeded_with_errors) help with interpretation but not with tool selection.

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