canvas_list_enrollments

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

No annotations are provided, so the description carries the full behavioral burden. It discloses a critical downstream dependency (enrollment_id is required to modify enrollments) and a dangerous silent-failure mode, which is high-value context beyond the schema. It does not cover pagination, return shape, or auth, but the failure-mode warning is the most important behavioral trait here.

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?

Three short paragraphs: purpose and key distinction first, the failure-mode warning second, then a clean Args block. Every sentence earns its place and the most decision-relevant information is front-loaded.

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 3-param, 0%-documented-schema tool with no annotations, the description supplies the role/state enumerations, the default resolution behavior, the sibling distinction, and the downstream dependency. An output schema exists, so return values need not be explained. Nothing an agent needs to call this correctly is missing.

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 0%, so the description must compensate, and it does: course_id is documented as numeric with a default fallback to CANVAS_DEFAULT_COURSE_ID, role enumerates the exact accepted values, and state enumerates its values with the empty-string semantics for 'all'. Without this, the schema fields are opaque strings.

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 states a specific verb and resource ('List enrollments') and immediately clarifies the critical distinction from its sibling canvas_list_students: enrollments are not users, and the enrollment_id is a different number from the user id. This is exactly the kind of disambiguation that helps an agent select the right tool.

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?

It gives explicit when-to-use guidance ('Fetch it here first') and a concrete when-not-to / failure mode ('passing a user id to canvas_remove_enrollment silently targets the wrong record or 404s'). It names the alternative tool (canvas_list_students) and explains why the agent should prefer this one for the mutation workflow.

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