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

Beyond the read-only annotations, the description adds meaningful behavioral context: no API key is needed, each leg has independent as_of/availability, and a chainless token yields no TVL rather than a fabricated value. These details materially change how an agent interprets results and are exactly the kind of non-obvious behavior worth stating.

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 dense sentences with no repetition: the first states source, scope, and metric window, and the second handles reporting semantics and edge cases. The most decision-relevant facts are front-loaded.

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 single-parameter tool with an output schema and annotations already covering safety, the description covers source, access, metrics, per-leg freshness, and missing-data behavior. An agent has everything needed to invoke it correctly and interpret its result shape.

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 schema already documents the symbol parameter, but the description adds useful semantics by explaining that the symbol determines the token's own chain and that chainless tokens affect the TVL leg. It stops short of listing accepted symbol formats or validation rules, so it improves on the schema without fully replacing it.

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 pinpoints the data source (DefiLlama), the exact metrics (7-day and 30-day changes in stablecoin supply and chain-specific DeFi TVL), and the token-scoping behavior. This makes it obvious the tool is a macro-liquidity lookup and clearly separates it from sibling tools like price_crosscheck and technicals_crosscheck.

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 implies the use case—checking macro liquidity without an API key—and even flags an edge case (no chain => no TVL), but it never explicitly says when to choose this over sibling tools or when it should be avoided. The guidance is situational rather than comparative.

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