get_market_sentiment

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

With no annotations provided, the description carries the full burden. It effectively describes the tool's behavior by specifying the output format (current value 0-100, classification categories, and 7-day history). However, it lacks details on rate limits, data sources, or update frequency, which would enhance transparency for a sentiment index tool.

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 in the first sentence, followed by a usage guideline. Both sentences are essential—the first defines the tool's function, and the second provides contextual application—with no redundant or wasted words.

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 has 0 parameters, 100% schema coverage, and an output schema exists, the description is complete. It clearly explains what the tool does (retrieves sentiment index data) and when to use it (alongside price data), which is sufficient for an agent to understand and invoke this tool correctly without needing additional details on parameters or return values.

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, focusing on output semantics. A baseline of 4 is applied since the schema fully covers the absence of parameters, and the description adds value by explaining what the tool returns.

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 explicitly states the tool retrieves the Bitcoin Fear & Greed Index, including current value, classification, and 7-day history. It clearly distinguishes this from sibling tools that focus on blockchain analysis, transactions, or price data, as it specifically targets market sentiment metrics.

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 guidance to 'Use this to gauge market sentiment alongside price data,' indicating when to use this tool (for sentiment analysis) and how it complements other data sources like price tools (e.g., get_btc_price). This clearly differentiates it from alternatives in the sibling list.

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