get_coin_market_cap_history

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

With no annotations provided, the description carries full burden for behavioral disclosure. It explains how market cap is calculated (price × circulation) but lacks critical details: it doesn't mention whether this is a read-only operation, what the response format looks like (e.g., time-series data), pagination behavior, rate limits, authentication needs, or error conditions. For a historical data tool with no annotation coverage, this is a significant gap.

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 efficiently structured in two sentences: the first states the purpose, and the second explains market cap calculation. It's front-loaded with the core function and avoids unnecessary fluff. However, the second sentence about calculation could be considered slightly redundant if the agent already understands market cap, but it's still concise.

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 complexity of historical data retrieval with 3 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., read-only nature, response format, error handling) and usage guidelines. While the schema covers parameters well, the overall context for an AI agent to use this tool effectively is insufficient.

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 the schema fully documents all three parameters (uuid, interval, limit) with descriptions, defaults, and constraints. The description adds no parameter-specific information beyond what's in the schema, such as examples or additional context about UUID lookup. Baseline 3 is appropriate when the schema does the heavy lifting.

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 retrieves historical market cap data for a specific coin, using the verb 'check out' and specifying 'historical market cap'. It distinguishes from siblings like get_coin_price_history or get_global_market_cap_history by focusing on coin-specific market cap history. However, it doesn't explicitly contrast with these siblings in the description text itself.

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 provides no guidance on when to use this tool versus alternatives like get_coin_price_history or get_global_market_cap_history. It mentions the endpoint but doesn't specify use cases, prerequisites, or exclusions. The agent must infer usage from the tool name and parameters alone.

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