aup_check_compliance

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

No annotations are provided, so the description carries the full behavioral burden and does so well: it discloses the return shape { allowed, policy_id, disclosure_id, violations[] } and clarifies the critical semantics that allowed=true means only these eight checks passed, not general compliance. It omits operational traits such as auth requirements or fetch failures when aup_url is unreachable.

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 dense sentences that are front-loaded with the core action and the check list; the return contract and exclusions follow. Every clause carries information, though the check enumeration is long enough that density borders on crowding.

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?

There is no output schema, so the description correctly compensates by naming the return fields and the exact meaning of allowed=true. Combined with the explicit non-coverage list, an agent can call this correctly; only operand-provision details (URL vs inline JSON behavior, error cases) are left to the schema.

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 aup_url (server-fetched), aup_json, and disclosure_json. The description adds no syntax or format guidance beyond the schema, which is the expected baseline when the schema does the heavy lifting.

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 (compare), two specific resources (AUP and Student AI Disclosure), and enumerates the eight checks performed, so the agent knows exactly what the tool does. The one gap is sibling differentiation: the sibling list contains a near-twin named 'disclosure_aup_check' plus 'aup_validate'/'aup_inspect', and the description never says how this differs from them.

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 gives a clear when-not scope: it explicitly lists what it does NOT verify (policy scope, tool/vendor requirements, parent consent, Tutor Cards, legal compliance) and states 'is not an enforcement decision', which tells the agent this is advisory only. It stops short of naming an alternative tool to use for the excluded concerns, so routing is left partly to inference.

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