get_financial_program_abnormal_recommendations

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 only states the action ('Get') without detailing traits such as whether it's a read-only operation, requires authentication, has rate limits, or what the output entails. While 'Get' implies a read operation, it lacks specifics on data freshness, pagination, or error handling, making it insufficient for a tool with no annotation support.

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, direct sentence: 'Get stocks abnormally recommended in financial programs.' It is front-loaded with the core action and resource, with no wasted words or redundant information. This makes it highly efficient and easy to parse for an AI agent.

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 that the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description's job is simplified. It adequately states what the tool does without needing to explain parameters or return values. However, it lacks context on behavioral aspects like data sources or limitations, which could be important for a tool fetching financial data, leaving some gaps in completeness.

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, meaning no parameters need documentation. The description does not add parameter information, which is acceptable since there are none to explain. It effectively communicates the tool's purpose without unnecessary details, aligning with the schema's completeness.

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 'Get stocks abnormally recommended in financial programs' states a clear verb ('Get') and resource ('stocks abnormally recommended in financial programs'), providing a basic purpose. However, it lacks specificity about what 'abnormally recommended' means (e.g., based on volume, price, or other metrics) and does not differentiate from siblings like 'get_abnormal_accumulated_notice_stocks', which might overlap in concept. This makes it somewhat vague but not tautological.

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 no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, nor does it refer to sibling tools for comparison. This leaves the agent without direction on appropriate usage scenarios, relying solely on the tool name and description for inference.

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