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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds 'Free' (no cost) and enumerates the returned statistics, which is useful context, but says nothing about rate limits, data recency, or the open-world behavior the annotation flags.

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?

Three compact, front-loaded sentences with no filler, and the 'Free' qualifier is placed first. Every clause carries information; it errs only on being terse rather than padded.

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?

For a low-complexity, read-only tool with one optional enum param and no output schema, the description does the necessary work by listing the returned fields. It is largely self-sufficient, with only the enum meanings and usage context left implicit.

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?

With one optional parameter and 0% schema description coverage, the description must carry the parameter meaning. It clarifies that 'state' is a filter and is optional, which is some value, but it does not explain the seven enum tokens (e.g., up_50pct_7d, funding_top5); those are only inferable from their names.

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 precise verb+resource: historical base rates for every crowd state, naming the exact statistics returned (sample size, median/spread of later returns, chance of run-ups). An agent knows what this returns. It does not, however, name or distinguish itself from related siblings like crowd_states or annalist_market_sample.

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 'Optional state filter' note and 'Free' tag imply when to reach for this tool, and the enum listing suggests filtering to a specific crowd state. But there is no explicit when-to-use/when-not framing or any routing to sibling tools that might also expose crowd-state data.

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