CoinGecko MCP Server

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

The description adds minimal behavioral context beyond the readOnlyHint annotation. It implies a read operation for querying data, which aligns with the annotation, but doesn't detail aspects like rate limits, error handling, or data freshness. The annotation covers safety, so the description meets a baseline by not contradicting it, but offers little extra insight.

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, clear sentence that efficiently conveys the core function without unnecessary details. It's front-loaded and avoids redundancy, though it could be slightly more structured by explicitly listing key parameters or use cases.

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's moderate complexity (5 parameters, no output schema) and the readOnlyHint annotation, the description is minimally complete. It covers the basic purpose but lacks details on output format, error conditions, or advanced usage, leaving gaps that could hinder effective tool invocation by an AI agent.

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 description mentions 'token contract addresses' and 'network', aligning with the required parameters, but doesn't explain parameter formats or interactions. With 60% schema description coverage, the schema documents some parameters (e.g., include_composition), but the description adds no additional semantic value beyond what's implied, resulting in an adequate baseline score.

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's purpose: querying token data based on contract addresses on a network. It specifies the verb 'query' and the resource 'multiple tokens data', making the function understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_tokens_networks_onchain_info' or 'get_addresses_pools_networks_onchain_multi', which reduces precision.

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. It mentions querying token data but doesn't specify scenarios, prerequisites, or exclusions. With many sibling tools available for token and network queries, the lack of comparative context leaves usage ambiguous.

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