Add Favorite Course

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

Adds real context beyond annotations: 'Only affects your own view' scopes the mutation to the caller's personal dashboard, which the hint flags alone (readOnly=false, destructive=false, openWorld=true) do not convey. It doesn't describe the response or whether re-starring is a no-op, which matters given idempotentHint=false.

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 sentences, the purpose and dashboard effect are front-loaded, and the reversal pointer comes last. No filler.

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 single-parameter personal-scope mutation with annotation coverage, the description supplies the scope caveat and the undo path. The only gap is return behavior, which is minor for such a simple toggle.

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% — the single course_id parameter already documents format ('12345') and provenance (list_courses). The description adds nothing about the parameter, so baseline 3 applies.

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?

States a specific verb (star/favorite) and resource (course), plus the visible effect ('shows on your Canvas dashboard'). The mutual exclusion with remove_favorite_course is named, so the agent can separate it from the sibling without opening a schema.

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?

Gives a clear condition for use (marking a course as favorite) and names the inverse tool for undoing it. It does not explicitly contrast with list_favorite_courses or say when *not* to favorite, but the context is unambiguous for a one-action tool.

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