get_announcements

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

No annotations are provided, so the description carries the full burden. It discloses behavioral traits like the return format (title, body, etc.) and that it fetches from instructors, but lacks details on permissions, rate limits, or whether it's read-only. This is adequate but has gaps, such as not specifying if it requires authentication or handles errors.

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?

The description is front-loaded with the core purpose, followed by return details and usage examples, all in two efficient sentences with zero waste. Every sentence adds value, such as clarifying the return fields and providing query examples, making it highly concise and well-structured.

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?

Given the tool's low complexity (1 optional parameter, no output schema, no annotations), the description is mostly complete: it covers purpose, returns, and usage context. However, it lacks output schema details (e.g., response structure) and behavioral aspects like error handling, which slightly reduces completeness for a tool with no annotations.

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 the schema already documents the single parameter (orgUnitId) with its optional nature and env var fallback. The description adds no parameter-specific information beyond what the schema provides, resulting in a baseline score of 3, as it doesn't compensate but also doesn't detract.

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 clearly states the specific action ('Get course announcements/news items from instructors') and resource ('announcements/news items'), distinguishing it from siblings like get_assignments or get_course_content. It explicitly lists the returned fields (title, body, created date, etc.), making the purpose highly specific and differentiated.

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 description provides clear context by listing example queries ('Any new announcements?', 'What did the professor post?', etc.) that indicate when to use this tool. However, it does not explicitly state when not to use it or name alternatives among siblings, such as get_course_content for general course materials, which prevents a perfect score.

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