get_fii_retail_divergence

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

With no annotations, the description bears full responsibility for behavioral disclosure. It details the signal logic, data source (quarterly NSE shareholding), and return fields including divergence_type, signal, confidence, interpretation, historical_implication, and raw data. It does not mention any side effects or rate limits, but as a read-only analytical tool, the description is sufficient.

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 organized into clear sections: introduction, signal conditions, example quote, data source, and args/returns. While it includes an illustrative example, it is not overly verbose. It front-loads the main use case effectively.

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?

Despite having only one parameter, the description covers the tool's purpose, behavior, input format, and output details comprehensively. The presence of an output schema is noted, but the description still explains the return structure, making the tool fully understandable for an AI agent.

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%, so the description must compensate. It explicitly defines the 'symbol' parameter as an NSE symbol and provides examples (HDFCBANK, RELIANCE, TATAMOTORS). This adds meaningful context beyond the schema's type-only definition.

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 it detects 'FII vs retail divergence' and describes it as the 'highest-conviction signal in Indian markets'. It uses a specific verb 'Detect' and clearly distinguishes the resource (FII and retail divergence on stocks). Among siblings, this is unique.

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 explains when to use this tool: for detecting divergence between FII and retail actions. It provides a concrete example with HDFC Bank and mentions the data source (public NSE shareholding disclosures). However, it does not explicitly state when not to use it or mention alternative tools.

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