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

With readOnlyHint and openWorldHint already declared, the description usefully adds the 30-day window, the per-agent breakdown, and that each recent call comes with the evidence it was graded on. It does not mention rate limits, freshness, or pagination behavior, but the added scoping is meaningful beyond the annotations.

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?

Two tightly written sentences: the first front-loads the data content and the second states the use case. No filler or redundancy.

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?

An output schema exists, so the description need not explain return shapes, and it correctly focuses on scope and purpose. For a zero-parameter read tool this is nearly complete, with only minor gaps around interpretation or staleness of the 30-day window.

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?

The tool takes no parameters and schema coverage is 100%, so there is nothing for the description to compensate for. Baseline 4 applies: no param semantics are needed and none are missing.

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 resource (per-agent grading accuracy of BUY/SELL/rug-warning calls over 30 days) with the concrete scope of the data. It is clear what 'track record' means, though it does not explicitly name a sibling tool to contrast with (e.g. get_signals), so differentiation is inferential rather than stated.

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?

'Use it to decide how much weight to give a signal' gives a clear decision context, effectively linking it to signal-consuming siblings like get_signals. It stops short of naming an alternative or an exclusion condition, so it is strong context but not full routing guidance.

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