client_sentiment

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

No annotations are provided, so the description must convey behavioral traits. It only states 'Get' which implies a safe read operation, but does not disclose any side effects, permissions, rate limits, or response handling. This is minimal disclosure 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?

A single sentence that front-loads the core action and scope. No wasted words, yet it conveys the key parameter distinctions.

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 read tool with two optional parameters and an output schema, the description covers the main invocation patterns. It does not explain edge cases like parameter precedence, but the output schema likely covers return format. Overall, sufficient for an agent to select and invoke correctly.

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 description coverage is 0%, so the description must add meaning. It does so by mapping the two parameters: 'all markets' corresponds to null market_id, 'one market' to a specific market_id, and 'related' to the related flag. This provides semantic clarity beyond the bare schema.

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 states the tool retrieves client sentiment, with explicit scope variations ('all markets, one market, or related markets'). This distinguishes it from sibling tools like market_details or historical_prices, which focus on different data types.

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 implies usage when sentiment data is needed, but does not explicitly say when to prefer this over alternatives or provide exclusion criteria. The scope phrasing gives some context for parameter usage, but no formal guidance on when to use versus other tools.

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