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

Annotations are absent, so the description carries the full burden and does so well: it discloses pricing (10 free calls/day, 1 credit = $0.02), auth mechanisms (x402 wallet payment via arguments.payment or X-PAYMENT header, strict HTTP-402 transport URL, Bearer tf_live_... token), a trial-credit path, and the subtle billing default when tier is omitted. Coverage limits (forward-only from launch, only publishers TensorFeed indexes on Base) are also stated.

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?

Opening sentence front-loads the resource and scope before any billing detail, and most of the length is load-bearing (pricing, auth, coverage limits). It still repeats the tier/payment explanation already present in the schema descriptions, and the final sentence bundles a URL-heavy trial-credit pitch that could be trimmed.

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?

With no annotations and no output schema, the description covers the essentials an agent needs to call it correctly: what is returned at each tier, the default tier, cost, and both payment paths. The main residual gap is the shape of the returned verdict/receipt fields, which is implied ('headline verdict', 'per-publisher ranking with volume share', 'AFTA-signed receipt') but not specified.

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%, so tier, window, and payment are already fully documented in the schema; the description's tier/window prose largely restates those semantics. It adds the cross-cutting rule that a payment or credits token silently promotes the tier to 'full', but otherwise is baseline-level against a complete schema.

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?

Names a specific verb+resource (a signed settlement-market ruling over TensorFeed's own on-chain x402/USDC settlement index on Base) and enumerates the dimensions it rules on: momentum vs. prior equal-length window, concentration, and leading publisher. It also scopes coverage ('publishers TensorFeed indexes on Base, forward-only from launch'), which distinguishes it from siblings like x402_publisher_verdict and benchmark_trust_verdict.

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 conditions for each mode: 'preview' is free with 10 calls/day/IP, 'full' costs 1 credit ($0.02) and adds the ranking/receipt, and the omit-tier auto-billing rule is spelled out. However, it never names an alternative sibling tool or says when to reach for this verdict versus x402_publisher_verdict, so routing between tools is left partly to inference.

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