compute_budget_proof

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states that the tool derives a score, label, and purchase-intent percentage from pricing, review-site, and intent-mention signals, which is honest about its main computation. However, it does not disclose how missing optional inputs are handled, how labels are assigned, or what role the hasNamedPricing boolean plays.

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 dense sentence that front-loads the outputs and then lists the contributing signal types. Every word adds useful information, and there is no filler, repetition, or unnecessary detail.

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 simple stateless computation tool, the description captures the core inputs and outputs in a compact way. Still, the lack of an output schema and annotations means more burden falls on the description; it does not explain the hasNamedPricing parameter, label thresholds, or edge-case behavior, leaving an agent to guess at some semantics.

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 0%, so the description must add parameter meaning on its own. It maps pricing hits, review-site hits, and intent mentions to three of the four schema parameters, which is helpful. It omits hasNamedPricing entirely, and the schema property names, though reasonably self-explanatory, are not enough to fully explain the boolean's influence on the calculation.

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 names a specific verb ('Compute'), a specific resource ('budget_proof_score'), and the exact outputs (score, label, purchase_intent_pct). It also identifies the input signal classes, making the tool's purpose clear even among many compute_* siblings. It does not explicitly contrast itself with siblings, but the resource name and outputs provide enough distinction.

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?

No guidance is given about when to use this tool versus any of the sibling compute_* tools or other alternatives. There are no inclusion/exclusion criteria, no context about typical workflows, and no mention of prerequisites. The description only says what the tool does, not when an agent should choose it.

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