social_get_market_sentiment

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals only that the result is aggregated from social data, but does not describe the response format, possible value range, update frequency, or limitations. The read-only nature is only implied by 'Get' and not explicitly stated.

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, front-loaded sentence with no filler, redundancy, or unnecessary detail. Every word contributes to defining the tool's purpose.

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 simple zero-parameter tool, the description covers the essential purpose, but with no output schema and no annotations, it should have stated what the returned sentiment data looks like (e.g., score, label). This omission leaves the agent guessing about the response, so it is complete enough only for basic selection, not full invocation confidence.

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 tool has zero parameters, so the input schema is trivially complete and no further parameter explanation is needed. The baseline for parameterless tools is 4.

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 uses a specific verb ('Get') and clearly identifies the resource ('overall crypto market sentiment') and data source ('aggregated from social data'). This distinguishes it from sibling tools like social_get_market_sentiment_history and social_get_news_sentiment, making its purpose 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 phrasing 'overall' and 'aggregated from social data' gives clear context that this tool is for a market-wide sentiment snapshot rather than per-coin or news-specific sentiment. However, it does not explicitly mention when not to use it or name alternative tools, so it falls short of a 5.

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