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

With no annotations, the description must carry behavioral disclosure. It does add useful behavior context: this is a 'processed analytics layer' returning a 'live computed signal' and it mentions a 0.01 fee via x402 on Base. However, the garbled 'Turns ra Price' sentence and lack of clarity about data source, latency, or side effects limit transparency.

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 short and front-loaded with the signal purpose, but the final sentence 'Turns ra Price 0.01 via x402 (USDC on Base)' appears truncated or corrupted. This structural defect prevents it from being a clean, effective description.

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?

The description lists output components and a price, but it does not clarify the target asset ('US stock short'), the meaning of 'short', the period unit for the 30-period calculation, or how to decide between this and related processed_* tools. Given no output schema and no annotations, these gaps are significant.

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%, so the schema already fully explains the only parameter, wallet. The description does not add meaningful parameter-level detail beyond the schema; the fee mention is not clearly tied to the wallet parameter.

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 says the tool 'get live computed signal' and lists the computed components: 30-period percentile rank, 4-period momentum, and a trend verdict. However, it refers broadly to 'financial markets' rather than US stock short, so the agent cannot tell this is specific to US stocks or 'short' signals from the description alone.

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?

No guidance is given about when to use this tool compared to the many processed_* siblings. There are no alternative tool names, exclusion criteria, or context cues beyond the tool name itself.

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