CoinGlass MCP Server

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

Annotations already provide strong behavioral hints (readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true), covering safety and idempotency. The description adds value by explaining the tool's utility ('understanding market concentration and finding arbitrage opportunities'), but does not disclose additional behavioral traits like rate limits, authentication needs, or data freshness beyond what annotations imply.

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 front-loaded with the core purpose, followed by utility context and specific examples. Every sentence earns its place: the first states the action, the second explains use cases, and the examples illustrate parameter usage without redundancy. It is appropriately sized for a tool with clear parameters and annotations.

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, rich annotations (covering safety and idempotency), 100% schema coverage, and the presence of an output schema (which handles return values), the description is complete enough. It provides purpose, usage context, and examples, leaving no critical gaps for an AI agent to understand and invoke the tool correctly.

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%, with clear descriptions for all parameters (action, symbol, range). The description adds minimal semantic context through examples (e.g., 'BTC OI by exchange'), but does not provide additional meaning beyond what the schema already documents, such as explaining the significance of 'by_exchange' vs 'exchange_chart' in market analysis.

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 with specific verbs ('Get Open Interest distribution') and resources ('across exchanges'), distinguishing it from siblings like 'coinglass_oi_history' (historical OI trends) or 'coinglass_market_data' (general market data). It specifies the exact data type (OI distribution) and scope (exchange-level), making its function unambiguous.

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 clear context for when to use the tool ('useful for understanding market concentration and finding arbitrage opportunities'), but does not explicitly state when not to use it or name specific alternatives among siblings. While it implies usage for OI analysis, it lacks direct comparison to tools like 'coinglass_oi_history' for temporal trends or 'coinglass_long_short' for position ratios.

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