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

Annotations already declare readOnly/idempotent/closed-world, so the safety profile is covered; the description adds behavior annotations cannot express — the empty-until-test state, the meaning of effectRatio (1.6 = 1.6× result), the 1–5 confidence scale, the post-count basis, and the re-check due date. With no output schema, this return-shape disclosure is exactly the missing behavioral context.

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 the purpose, then the returned fields, then usage routing — a sensible order. The field enumeration sentence is long, but given there is no output schema each clause carries information an agent needs to interpret results, so only minor trimming is possible.

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?

Covers everything needed for a zero-parameter read with no output schema: what the data is, how to read each field, the empty-state precondition, which sibling creates the data, and which sibling handles the adjacent scoring task. Nothing required to call or interpret it is missing.

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 tool takes no parameters, so there is no parameter semantics to explain and the baseline is 4. The description correctly spends its words on the returned fields instead.

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 (list learned hook rules per account) and immediately differentiates the artifact from generic advice by naming its provenance: real-audience hook tests. It also names what it is not (check_draft scores a caption; create_hook_test produces the data), so an agent can place it among siblings without opening a schema.

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 when-to-use ("Read these before writing a draft"), an explicit precondition ("The list is empty until a hook test has concluded — create_hook_test starts one"), and an explicit alternative for the adjacent use case ("To score one particular caption against the rules, use check_draft instead"). Both routing decisions are stated, not inferred.

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