buda-mcp

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: the scoring range (-100 to +100), the three calculation components with exact weights, the return format (score, label, component breakdown), and that it's based on 24-hour data. It doesn't mention rate limits, authentication needs, or data freshness, but provides substantial operational context.

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 explains the computation methodology and return values, the second provides a concrete usage example. Every element serves a purpose with no wasted words, making it easy to parse and understand quickly.

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 single-parameter tool with no output schema, the description provides excellent context about what the tool does, how it works, and what it returns. The only gap is the lack of explicit output structure details (though the return components are mentioned), but given the tool's relative simplicity and the rich behavioral disclosure, this is largely complete.

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% for the single parameter (market_id), so the schema already documents it adequately. The description doesn't add any additional parameter semantics beyond what's in the schema, maintaining the baseline score of 3 for high schema coverage situations.

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 computes a composite sentiment score for a Buda.com market, specifying the exact components (price variation, volume, bid/ask spread) and their weights. It distinguishes from siblings like get_market_summary or get_technical_indicators by focusing specifically on sentiment analysis rather than general market data or technical indicators.

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 this tool through the example question 'Is the BTC-CLP market currently bullish or bearish?' This implies it's for assessing market sentiment rather than raw data retrieval. However, it doesn't explicitly state when not to use it or mention specific alternatives among the sibling tools.

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