List Watched Course Sections

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

Annotations already declare readOnly, idempotent, non-destructive and openWorld. The description adds real behavioral context beyond them: the data source is local state rather than OBS, and staleness is tied to the last check call. It does not discuss pagination or output shape, but output schema exists.

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 sentences, zero waste. The core listing purpose is front-loaded and the staleness caveat follows immediately as the most decision-relevant detail.

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 zero-parameter list tool with an output schema and full annotation coverage, the description supplies everything needed: what is listed, the source of truth, and why the data may be stale. Nothing an agent needs to invoke it 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. No misleading parameter hints are given.

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 (List) and resource (sections on the local seat watch list) plus exactly what fields are returned (term added, last stored observation). This clearly separates it from the sibling check_watched_course_sections, which is named directly.

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 clause about reading only local state and numbers being 'as old as the last check_watched_course_sections call' tells the agent when this tool's output is fresh versus stale, effectively pointing to the refresh sibling. It stops short of an explicit 'use this when X, use check_... when Y' directive.

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