token_market_data

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

Despite annotations already declaring readOnlyHint/idempotentHint, the description adds substantial value beyond them: 'free', 'no API key', 'nothing signed or spent', and explicit failure behavior on unknown symbols or unreachable upstreams. This exceeds the annotation baseline by disclosing cost, auth, and error semantics.

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 core capability, then structured with 'Use when' / 'Not for' / 'Returns' / 'Example response' / 'Price'. Every sentence earns its place; no repetition or filler.

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 read-only data tool with no output schema, the description provides return fields, an example response, cost/auth information, and failure modes—everything an agent needs to call it correctly and interpret the result.

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 100%, so the baseline is 3. The description adds meaning by implying a token pair (token_a/token_b) and demonstrating the pair in the example response (ETH/USDC), which clarifies that both tokens are required and how they interact—beyond the schema's terse field descriptions.

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 states a specific verb+resource ('Get market cap, 24h volume, ATH, and price change for any token') and explicitly distinguishes itself from the sibling orderbook_depth and token_price. An agent can tell exactly what this tool returns without opening any schema.

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?

Explicit 'Use when' and 'Not for' clauses name the alternative tools (token_price for spot price, orderbook_depth for pool liquidity) and the exact conditions that select them. Nothing is left to inference.

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