hb_route_evaluate

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

With no annotations, the description carries the full burden. It does disclose a meaningful behavioral trait: this feeds a routing feedback loop / learning process, so an agent can infer it mutates routing state and affects future selections. It does not say whether the effect is immediate, persistent, or reversible, which leaves a gap for a write-like operation.

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?

It is a single, front-loaded sentence with no filler or repetition. It is efficient, though the brevity is partly why other dimensions are thin rather than a sign of strong structure.

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?

For a state-mutating learning tool with no annotations and no output schema, the description omits what the rating does, what is returned, and its prerequisite relationship to hb_route_select. The schema covers the inputs, but the behavioral contract an agent needs before invoking it is largely 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?

Schema description coverage is 100% and the schema already defines both parameters (route_id, quality with a 0-1 range). The description adds no syntax, format, or constraint details beyond the schema. This meets the baseline 3 when structured fields do 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?

The description states a verb ("Rate") and a target ("a response for routing feedback loop"), so the general purpose is inferable. However, "a response" is ambiguous and it does not explicitly distinguish itself from close siblings like hb_route_select or hb_route_stats. The purpose is vague-but-directional rather than specific.

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?

There is no explicit statement of when to call this tool, what must precede it (e.g., a prior hb_route_select), or which sibling to use instead. The "epsilon-greedy learning" parenthetical is context, not guidance. The agent must infer usage entirely from the name.

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