List the Canvas courses marked as favorites on your dashboard, so you can quickly find the classes you use regularly.
List the courses you starred as favorites in Canvas (the ones on your dashboard). For every course use canvas_courses.
| Name | Required | Description | Default |
|---|---|---|---|
| raw | No | true: Canvas's unmodified JSON (UTC times, HTML). | |
| page | No | Page to fetch: a number, or the next_page value returned by the previous call. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered structurally. The description adds only the semantic clarification that 'favorites' equals dashboard stars, and says nothing about pagination behavior or how many results come back despite exposing a page parameter.
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?
Two short sentences with the scoping statement front-loaded and the sibling routing second; every clause carries information and there is no filler. The slightly clipped phrasing of the second sentence costs nothing in clarity.
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 parameterless, read-only list tool whose annotations fully cover safety and whose schema fully documents both parameters, the description is nearly sufficient as-is. The only gap is that it does not hint at the shape of the returned course list, which matters slightly more given there is no output schema.
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 description coverage is 100%, so both 'raw' and 'page' are already documented in the input schema, including the bookmark-style next_page format. The description adds no meaning beyond that, so the baseline 3 for schema-documented parameters 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?
The description gives a specific verb ('List') and a narrowly scoped resource ('courses you starred as favorites in Canvas'), and the parenthetical 'the ones on your dashboard' pins down the exact meaning of favorites. It also names the sibling canvas_courses as the broader alternative, so an agent can distinguish the two without opening either 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?
It explicitly routes the agent to canvas_courses when the intent is 'every course' rather than starred favorites, which is real when-to-use guidance. The final sentence is phrased a little telegraphically ('For every course use canvas_courses') and there is no explicit statement of when-not to call this tool at all, keeping it short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.