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

Goes well beyond the readOnlyHint/openWorldHint annotations: it discloses determinism, absence of LLM/trained model, the paper it is and is not based on, exact pricing ($0.15 USDC via x402 on Base mainnet), and the concrete failure path (unpaid call returns PaymentRequired, retry with signed payload in _meta['x402/payment']). That is precisely the behavioral context an agent needs to invoke successfully.

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 operation and mechanism, then the trust note, then the payment flow. Four sentences, all load-bearing except the citation disclaimer, which is defensible but slightly padded.

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 stateless paid computation with no output schema, the description covers mechanism, determinism, cost, and the payment retry protocol. It stops short of describing the shape of the ranked result (sensor_id + score, top_k entries), which the absence of an output schema leaves partially inferred.

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 documents top_k, window format (URL-encoded JSON array, max 20 entries, baseline fields), and anomaly_event_id echo semantics. The description only restates that the window is caller-supplied, adding no syntax or constraint beyond the schema, so the baseline 3 applies.

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 ('ranks which sensors most likely drove a reported anomaly') plus the exact mechanism ('z-score deviation from each sensor's own baseline'). This is unlike any sibling, which are all report/exposure/dossier getters, so the agent can distinguish it immediately.

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?

Implied usage is clear from the precondition ('given a caller-supplied telemetry window') and the method note (per-sensor baseline required), but there is no explicit when-to-use/when-not-to-use statement and no named alternative among siblings. The agent must infer the frame of applicability.

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