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

With no annotations, the description carries the full burden. It discloses the returned metrics (hit rate, Wilson intervals, Brier score, independent samples) and that access is free, but says nothing about auth requirements, rate limits, or whether results are cached. Adequate but not rich.

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?

One dense sentence, front-loaded with what is returned and the free-access note. The colon-separated metric list is efficient, though the punctuation reads slightly awkwardly.

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?

No output schema exists, so listing the metrics is genuinely useful. However, with zero required parameters, the description never says what happens when symbol is omitted (all-symbol aggregate vs. error), which is the one behavior an agent must know before calling.

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% with an enum for symbol, so the schema already documents the parameter fully; baseline 3 applies. The phrase 'by symbol' adds only a faint hint that the symbol scopes the breakdown rather than being required.

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?

States a specific resource and scope: graded accuracy metrics for every published signal bias. It is clearly distinguishable from get_signal_bias (current bias) and get_target_probability, though it never names a sibling to sharpen the boundary.

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 when-to-use, when-not-to-use, or alternative tool is mentioned. The '(free)' tag hints at a tiering distinction but the agent is left to infer that this is the historical-performance counterpart to the other signal tools.

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