list_academic_programs

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'List' and provides parameter descriptions; it does not mention that the operation is read-only, whether results are paginated, or any error conditions. This is a significant gap for an unannotated 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-line purpose followed by a compact, well-organized Args block. Every sentence provides useful information without redundancy, and the key purpose is front-loaded.

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 that an output schema exists, the description need not explain return values. It covers all input semantics and the primary use case. It could mention whether results are sorted or limited, but the limit parameter and default are in the schema. Overall it is sufficient for an agent to call 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?

The description includes an Args block that explains each parameter's meaning and constraints, such as query being a case-insensitive filter and credential_level being a code from 1 to 8. It also tells the source of school_id. Since the schema provides no parameter descriptions (0% coverage), this fully compensates and goes beyond the schema's type definitions.

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 verb 'List' and the resource 'College Scorecard fields of study for one U.S. institution.' It distinguishes itself from siblings like search_us_colleges (which searches for institutions) by emphasizing it operates on a single, known institution. The scope is unambiguous.

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 indicates that school_id is returned by search_us_colleges, implying a workflow of first finding a school then listing its programs. It does not explicitly mention alternatives or exclusions, but the context makes it clear when this tool is appropriate.

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