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

Beyond the readOnlyHint annotation, the description discloses that text is returned as published and not parsed into eligibility rules, which shapes caller expectations. It also clarifies the provenance as official subject outlines.

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, front-loaded with the core purpose and followed by a key limitation. No redundant wording.

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?

The description makes clear what the tool returns (raw prerequisite text) and its source, which is the key context absent from the schema. There is no output schema, but the simple return nature is sufficiently conveyed despite the many filtering parameters.

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 descriptions cover most parameters (term, as_of, cursor, school_code, snapshot_id, source_code, outline_term_code), and the description adds little parameter-specific meaning. The required course_code and limit/fields lack descriptions, but their purpose is largely inferable from names and enum values.

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 action ('Get raw prerequisite text') and source ('official subject outlines'), clearly distinguishing it from parsing eligibility rules. The sibling set includes multiple Seneca tools, and this one is unmistakably about raw prerequisite text.

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 usage when raw prerequisite text is needed and notes that eligibility rules are not parsed, but it does not explicitly reference alternatives such as seneca_get_course or search tools. No clear when-not or alternative routing is provided.

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