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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful extra context beyond annotations: it costs 0.004 USDC, is deterministic, evidence-bounded, signed, and uses transparent sample-aware statistics. This gives the agent important expectations about side effects and output characteristics.

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 short and front-loaded with the core action and scope. The phrasing is slightly awkward due to the semicolon and standalone cost token, but every clause adds useful information: purpose, method, fee, and behavioral guarantees.

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?

An output schema exists and annotations cover safety, so the return shape and read-only nature are handled. However, the description does not state what inputs are needed and gives no usage context to distinguish it from sibling estimator/predictor tools. This leaves the agent short of what it needs to invoke the tool correctly from the open input 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?

The input schema defines no named parameters but permits an open object with additionalProperties and minProperties 1. Although zero defined parameters normally lowers the burden, the open schema means the description should clarify what inputs are expected (e.g., provider identifier or sample data), and it does not. The description names output domains rather than input requirements.

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 uses a specific verb ('Estimate') and names the resource and scope: provider success, quality, latency, and cost. It is clear about what the tool computes, though it does not explicitly differentiate itself from sibling predictors like sla_risk_predictor or execution_cost_estimator.

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 no guidance on when to prefer this tool over alternatives, nor does it mention exclusions or complementary tools. A caller is left to infer that this is for provider estimation, but there is no context about selecting it among the many prediction/estimation siblings.

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