Bitcoin-MCP-Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior by detailing the return format (string with structured metrics), data sources (CoinGecko and Alternative.me), and temporal scope (7-day history). However, it doesn't mention potential limitations like rate limits, data freshness, or error conditions, which keeps it from a perfect score.

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 well-structured and front-loaded, starting with the core purpose, followed by a detailed breakdown of return metrics, and ending with use cases. Every sentence adds value without redundancy, and the use of bold headings enhances readability while keeping the text compact and efficient.

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 complexity (sentiment analysis with multiple metrics), no annotations, and an output schema present, the description is complete. It thoroughly explains the return values (community sentiment and Fear & Greed Index history), data sources, and use cases, providing all necessary context for an agent to understand and invoke the tool correctly without needing to rely on the output schema alone.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately omits parameter details, maintaining focus on the tool's purpose and output. A baseline of 4 is given since the description compensates for the lack of parameters by thoroughly explaining the return value semantics.

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 a comprehensive sentiment analysis') and resources ('Bitcoin market'), distinguishing it from siblings like get_bitcoin_market_data or get_bitcoin_price_usd by focusing on psychological metrics rather than raw data. It explicitly mentions the data sources (community voting and Fear & Greed Index), making the scope 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 explicit usage guidelines with a dedicated 'Use cases' section that states when to use this tool ('gauge overall market sentiment, understand investor psychology, or determine if the market is in fear or greed mode'). This clearly differentiates it from siblings that provide price, network, or transaction data, offering direct alternatives for different needs.

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