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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds material context beyond that: output is counts only, grouped by Canvas item type, with no item content — which meaningfully shapes how the agent should interpret the result.

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 tight sentences, front-loaded with the core action and return shape, ending with the workflow guidance. Every sentence earns its place with 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?

With no output schema, the description carries the return-value burden and does so adequately — it explains the counted dimensions and the grouping. It stops short of describing the exact response shape, but for a summary tool this is close to complete.

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% and the single parameter (only_active_courses) is fully documented in the schema. The description adds no additional parameter semantics (e.g. how concluded courses affect counts), so the 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 (count) and resource (cross-course activity stream) scoped to the authenticated student, and names the unit of aggregation (grouped by Canvas item type). It clearly distinguishes itself from the full-stream sibling by emphasizing counts-only with no item content.

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?

Explicitly positions itself in a workflow: 'a good first call in a daily workflow to check is there anything to look at? before fetching the full stream.' This routes the agent relative to the heavier stream-fetch sibling, though it describes rather than names that alternative directly.

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