Crypto / text sentiment scorer

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

No annotations provided, so description bears full burden. It mentions using an LLM and returning a score and label, but does not disclose limitations, latency, error cases, or side effects. Could be more transparent.

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 two concise sentences plus a usage instruction. No wasted words, key information front-loaded. Very efficient.

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 no output schema, the description mentions the return format. It is complete for a simple sentiment tool, covering inputs, outputs, and usage constraints. No gaps.

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%, baseline 3. The description adds clarity by explaining parameters and emphasizing mutual exclusivity ('EXACTLY ONE'), which goes 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 clearly states it provides a sentiment score (-1 to +1) with a label, for either raw text or a crypto asset's recent price action. This distinguishes it from siblings like crypto_regime or factcheck.

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 explicitly says to provide exactly one of `text` or `asset` and lists valid assets. It also mentions use cases (trading signals, news pipelines). However, it lacks explicit when-not-to-use or comparison with siblings.

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