sentiment_all

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses only the scope (combined sentiment from three sources) but says nothing about the return format, authentication requirements, response structure, rate limits, or any potential side effects. For a tool with one parameter, this is minimal and leaves the agent guessing about what to expect.

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 clear sentence that front-loads the verb and resource. There is no wasted words or redundant information. It is appropriately sized for a simple tool with one parameter.

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?

Without an output schema and without annotations, the description should at least hint at what the agent will receive in the response. It only states what the tool does, not what the response contains (e.g., sentiment scores, time ranges, or the structure of the combined data). This makes the tool's behavior opaque and incomplete for an agent deciding whether to call it and how to interpret the result.

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 100%, with the parameter 'ticker' described as 'Stock ticker'. The description adds no extra meaning beyond what the schema already provides, such as format, examples, or constraints. The baseline of 3 is appropriate because the schema handles the parameter documentation adequately.

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 states a specific verb and resource: 'Get combined sentiment (social, news, analyst) for a ticker'. It clearly identifies the tool's function and distinguishes it from the sibling tools sentiment_social, sentiment_news, and sentiment_analyst by being the combined version. No ambiguity exists about what the tool does.

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 you need all three sentiment types combined—but it does not explicitly state when to use the individual sentiment tools instead. No alternatives or exclusions are mentioned, leaving the agent to infer the scenario from the word 'combined' rather than receiving clear guidance on tool selection.

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