get_sentiment_state

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

No annotations are provided, so the description carries full disclosure burden. While it describes output content, it fails to disclose behavioral traits: read-only safety, data freshness (real-time vs cached), rate limits, authentication requirements, or error conditions. The word 'Get' implies reading, but explicit safety confirmation is absent.

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?

Single, well-structured sentence that front-loads the action and resource, followed by specific enumerated components. Every clause earns its place by disambiguating the return payload with concrete examples.

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 the tool has no parameters and no output schema, the description adequately compensates by enumerating the four key data components returned (Fear & Greed Index, trend, signals, opportunities). For a simple read-only data retrieval tool, this is sufficiently complete.

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?

Input schema has zero parameters. Per evaluation rules, zero parameters establishes a baseline score of 4 since there are no parameter semantics to describe beyond the 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 uses a specific verb ('Get') and resource ('crypto sentiment state'), and enumerates exact data components returned (Fear & Greed Index, 7-day trend, contrarian signals, extreme opportunities). It effectively distinguishes this from generic market data tools by specifying these unique sentiment metrics.

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 lists what data is returned but provides no guidance on when to select this tool over siblings like get_crowd_intelligence, get_narrative_pulse, or get_alternative_signals. No prerequisites, filtering conditions, or decision criteria are mentioned.

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