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

No annotations are provided, so the description must disclose behavioral traits. It states the operation is a 'Get' (read-only) and lists timeframes, which conveys the core behavior. However, it does not mention data freshness, pagination, or the structure of 'trend data,' leaving some behavioral details undisclosed.

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 a single sentence, front-loaded with the verb and key resource, and contains no wasted words. It is concisely structured and easy to scan.

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 the description should explain return values. It mentions 'historical probability changes and trend data' but does not detail the shape, units, or components of the trend data. This leaves some ambiguity, though it is adequate for a simple two-parameter tool.

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 schema covers 100% of parameters, including descriptions for market_id and an enum with a default for timeframe. The description repeats the timeframe enums ('1h/24h/7d/30d') but adds no extra meaning beyond what the schema already provides, so the baseline 3 is appropriate.

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 begins with 'Get,' a specific verb, and identifies the resource as 'historical probability changes and trend data for a market' with explicit timeframes (1h/24h/7d/30d). This clearly distinguishes it from sibling tools like get_probability (which likely returns current values) and get_market_stats.

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 implies this tool is for historical trend analysis with timeframe options, providing clear context on when to use it. However, it does not explicitly name alternatives or state when not to use it, but the word 'historical' effectively differentiates it from current-probability tools.

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