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

Annotations already declare readOnly, non-destructive, open-world behavior; the description adds genuinely new context: aggregation across 31 sources, per-story computed fields, a per-call price of USD 0.003, the x402/USDC-on-Base payment rail, and the fact that failed calls are not charged. That billing-on-failure detail is exactly the kind of trait annotations cannot express; only the payment mechanics (e.g. whether a payment header must be supplied) remain vague.

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?

Two sentences with no filler: the capability and its distinctive outputs come first, the cost/payment caveat second. Every clause carries information an agent needs.

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 output schema, the description usefully enumerates the returned shape (impact score, outlet count, price reaction) and discloses cost, which is the main risk of an accidental call. Minor gaps remain around default result count when limit is omitted and what an unfiltered call returns, but nothing that would cause a wrong invocation.

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 both parameters (limit, token) are described in the schema, so the schema carries the semantics. The description adds no additional meaning about whether token filters to one asset or what omitting it returns — baseline 3.

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 resource and scope ('Top crypto stories now from 31 sources') and enumerates the distinctive fields returned (impact score, outlet count, price reaction), so an agent knows exactly what it gets. It never contrasts itself with adjacent siblings such as sentiment or sentiment_free, so differentiation is inferred rather than stated.

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?

Usage is only implied by the word 'now' — an agent can infer this is for current news rather than the sentiment or prices tools, but no explicit when-to-use or when-not-to-use guidance is given. The cost/payment sentence is an operating constraint, not selection guidance.

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