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

With no annotations provided, the description carries the full burden. It does well: discloses it's a paid tool with the pricing range, funding mechanism (x402), supported chains, explains the scoring rule is disclosed per-response for reproducibility, and clarifies it's computed data not a relay. This is strong behavioral disclosure for a tool with zero annotations.

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 a single dense paragraph covering several topics (what it does, products, pricing, reproducibility). It's reasonably efficient but mixes marketing-style language ('disclosed indicator', 'supply-stress score per growing belt') with functional details, and could be restructured with clear breaks between purpose, products, pricing, and behavior.

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?

Given the tool has only 1 parameter, no output schema, and zero annotations, the description provides meaningful coverage: product enumeration, pricing, chains, payment mechanism, and reproducibility guarantee. The main gaps are per-product output descriptions and more precise parameter semantics, but for a 1-param tool it's fairly complete.

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 coverage is 0%, so the description must compensate for the single 'product' parameter. It does enumerate valid product values (market_brief, gas, yield, commodities), which is helpful. However, it doesn't describe the default behavior, what happens if product is omitted, the expected output structure per product, or any constraints on the product values.

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 clearly states the tool computes market/commodity indicators rather than relaying raw data, and lists the product types (market_brief, gas, yield, commodities). The purpose is specific and distinguishable from siblings like market_history, though it doesn't explicitly name a sibling for comparison.

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 usage context (paying for computed indicators, not raw relay), and the sibling list suggests market_history might be the alternative for historical data. However, there is no explicit when-to-use vs when-not-to-use guidance or named alternative tool.

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