Get university info

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

Annotations already declare readOnly, idempotent, non-destructive, open-world, so the safety profile is covered. The description adds value annotations do not: the return type varies by aspect (JSON vs. raw image bytes for 'logo'), which materially affects how an agent handles the response. It does not mention rate limits or failures, keeping it short of a 5.

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?

Front-loaded with purpose, then routing, then the aspect legend, which is the right order. The fragment 'University aspect.' is redundant filler before the list, and the legend is dense but every entry carries distinct meaning.

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?

No output schema exists, so the description must convey return shape, and it does at a coarse level (JSON per aspect, image bytes for logo). Given eight aspects with heterogeneous payloads, it could say a bit more about what each aspect returns, but an agent has enough to select and invoke correctly.

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 coverage is only 50% and the enum values carry no per-value descriptions in the schema, but the description compensates fully by defining all eight aspect values (detail, rasio, mahasiswa, waktu-studi, riwayat, biaya-kuliah, fasilitas, logo). The id_pt constraint ('copied exactly from a search_pddikti result, do not guess') is in the schema and reinforced by the workflow implied here.

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 and resource ('Fetch one aspect of a single university ... as JSON, or its logo as an image') and scopes it to a single institution. It explicitly distinguishes itself from the two sibling tools an agent would most likely confuse it with.

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?

Gives explicit positive usage ('profile, accreditation, and history questions about one university') and explicit exclusions with named alternatives ('for its study programs or lecturers use get_university_study_programs or get_university_lecturers'). Nothing is left to inference.

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