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

With no annotations provided, the description carries the behavioral transparency burden. It adds valuable context: the $0.02 per-call cost, x402 payment/settlement requirement, optional API-key auth paths, and the 'educational data, not financial advice' caveat. It does not explicitly state that this is a read-only/no-side-effect operation or describe rate limits, but the payment/auth behavior is disclosed.

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, then pricing, caveats, payment/auth details, and a pointer to the free catalog. Every sentence adds useful information, though the payment section is somewhat long. Overall it is appropriately sized for an API with nontrivial access requirements.

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 one-parameter tool with no output schema and no annotations, the description covers pricing, authentication methods, data sources, and the educational nature of the output. It does not specify the exact time window of 'recent' sentiment or output shape, but these are partially captured by the described content. The description is sufficiently complete for the tool's complexity.

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 coverage is 0% and there is only one required parameter, 'symbol.' The description adds the meaning that a symbol is a 'ticker' and that the call is for a single symbol, but it does not provide format guidance, examples, or constraints beyond that. Given the low coverage, more parameter semantics were needed.

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 identifies a per-symbol social sentiment tool: 'recent sentiment/retail signals (bullish vs bearish counts + net bias) merged with social-intelligence ideas' for 'one ticker.' This verb-like purpose distinguishes it from sibling tools like get_composite_signal or get_symbol_tearsheet.

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?

Usage context is implied through 'per-symbol' and 'for one ticker,' indicating this is for single-symbol sentiment queries. However, there is no explicit guidance on when to choose this over alternatives, no exclusions, and no named comparable tools.

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