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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful behavioral context beyond that by warning that the full payload is large and that `market_data`, `community_data`, `developer_data`, `tickers`, `sparkline`, and `localization` are heavy sections that should be left off unless needed. This is valuable operational transparency that the annotations do not provide.

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 longer than average but earns its length: it front-loads the primary return contents, then provides differentiation guidance and payload-size advice. It could be slightly tighter, but no sentence is filler and the structure flows logically from what-the-tool-returns to when-to-use-it.

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 complex read tool with an output schema, the description is complete enough: it covers the full scope of returned data, warns about payload size, suggests which flags to disable, and routes to the correct siblings. The existing output schema handles return-value structure, so the description does not need to restate that. No critical calling context appears missing.

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 low (14%), so the description carries a heavy burden. It identifies the boolean parameters as controlling heavy sections and advises disabling them unless needed, but it does not explain what each flag semantically includes (e.g., what `community_data` or `developer_data` contains). The `id` parameter's meaning is largely left to the schema, which already documents the coin ID and example. Overall, the description partially compensates but does not fully fill the gap left by the sparse schema.

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 returns everything CoinGecko holds on a single coin selected by `id`, and enumerates the key sections (`description`, `links`, `image`, `categories`, `platforms`, `market_data`, etc.). It differentiates itself from sibling tools by naming alternatives for price tables and contract-address lookups, so an agent can identify it confidently.

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?

It explicitly says 'Use it for a coin profile' and gives concrete routing guidance: for a price table across many coins use `get_coingecko_coins_markets`, and for lookup by contract address use `get_coingecko_token_data`. It also advises leaving heavy optional sections off unless needed, which is actionable usage guidance.

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