get_historical_bars

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

No annotations are provided, so the description bears full responsibility. It describes a read operation but omits critical details like data range (how far back), rate limits, pagination, or whether bars are intraday. This lack of information could lead to incorrect expectations.

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?

Single sentence, no wasted words, front-loaded with the core action. However, the extreme brevity risks under-specification; slightly more detail would improve without sacrificing conciseness.

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?

Given 3 parameters, no output schema, and no annotations, the description is minimal. It fails to explain return format (e.g., OHLCV with timestamps), data availability, or behavior for missing data. More context is necessary for an agent to use the tool correctly.

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 all three parameters (symbol, timeframe, count) are already documented. The description adds 'OHLCV', which clarifies bar content, but does not elaborate on parameter constraints or usage beyond the schema. 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 clearly states the verb 'Get' and the resource 'historical OHLCV bars for futures contracts', specifying the data type (OHLCV) and instrument class. It sufficiently distinguishes from siblings like get_futures_quote (single quote) and batch_download, but lacks explicit differentiation from timeseries_get_range.

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 on when to use this tool versus alternatives (e.g., timeseries_get_range, get_futures_quote). With many sibling tools, the absence of context for selection criteria hinders an AI agent's decision-making.

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