earnings_transcript_sentiment

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 says 'Get sentiment analysis' without specifying the output format (e.g., numerical score, textual summary), whether this is a read-only operation, or any other side effects or prerequisites. This is a significant gap for a tool that returns structured data with no output schema.

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, front-loaded sentence with zero fluff. It conveys the core purpose efficiently and does not waste words. This is an appropriate length for a simple lookup-style tool, and the structure is adequate.

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 tool with 3 required parameters and no output schema, the description is insufficiently complete. It does not describe what the sentiment analysis returns (e.g., a score range, sentiment categories, or a detailed report), nor does it mention any edge cases or caveats. An agent would not know what to expect from the tool's response, making it hard to integrate results into a workflow.

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 100%, so all three parameters (ticker, year, quarter) are already documented in the input schema. The description adds no additional meaning about how these parameters interact or what formats are expected beyond the examples already present in the schema. Since the schema does the heavy lifting, a baseline 3 is appropriate.

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 sentiment analysis of an earnings call transcript.' This clearly distinguishes it from 'earnings_transcript' (which presumably retrieves the raw transcript) and 'sentiment_news'/'sentiment_analyst' (which cover other sentiment types). However, it does not explicitly name or differentiate sibling tools, so it lacks the explicit comparison that would earn a 5.

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?

There is no guidance on when to use this tool versus alternatives like 'earnings_transcript' or the broader 'sentiment_*' tools. The description only states the action, leaving the agent to infer context from the name and sibling list. No exclusions or conditions are provided, so an agent cannot determine when not to use it or which alternative to prefer.

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