List course subjects

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

No annotations are provided, so the description carries full burden. It discloses the tool returns subject codes with optional name filtering and cites Purdue.io as source, but does not mention whether subjects are sorted, include inactive codes, or require authentication. The description is adequate but lacks depth for a data discovery tool.

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 a single sentence plus a source attribution, containing zero fluff. Every word adds value: it specifies the domain (Purdue), the data (subject codes), examples (CS, MA, ENGR), the optional filter, and the source. Highly efficient.

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 is simple (one optional param, no nested objects, no output schema), the description sufficiently explains what the tool returns and its optional filter. It doesn't include pagination or sort order, but for a list of subject codes this is likely unnecessary. The source attribution adds credibility. Complete for its simplicity level.

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% for the single parameter 'query', and the description mentions it filters by name or abbreviation, which adds context beyond the schema's 'Filter by name or abbreviation'. However, since there is only one optional parameter and the schema already describes it, the description's additional value is minimal, baseline 3 is appropriate.

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 tool lists all course subject codes at Purdue (specific examples given: CS, MA, ENGR) and mentions an optional filter by name. It distinguishes itself from sibling tools like 'list_terms' and 'search_courses' by focusing on subject codes rather than courses or terms.

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 implies the tool returns unfiltered subject codes unless a query is provided, but does not explicitly state when to use this tool vs siblings (e.g., when to call this before 'search_courses'). No explicit exclusions or alternatives are mentioned, though context signals show many sibling tools exist that might need this subject data.

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