get_chart

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds useful context by specifying that the tool returns unprocessed OHLCV data and lists the returned fields, but it does not disclose ordering, pagination, or data-range behavior. This adds some value beyond the annotations but leaves behavioral gaps.

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 concise sentences deliver the core purpose, field list, and the alternative tool routing without any filler or repetition. The primary action is front-loaded and every sentence earns its place.

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 moderate-complexity read-only data tool, the description covers the essential selection criteria (raw vs. calculated, field list) and the schema covers parameters. With no output schema, the field enumeration partially compensates for the lack of a structural return description; the main omission is ordering/pagination, but the tool remains callable correctly from the provided context.

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 description coverage is 100%, so all three parameters (symbol, limit, interval) are already documented in the schema, including the interval enum and the 500-candle maximum. The description itself does not add parameter-level meaning beyond saying the result is raw OHLCV, so a baseline of 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 states a specific verb ('döner' = returns), the resource (raw OHLCV candles for a symbol), and enumerates the exact fields (open, high, low, close, volume, timestamp). It also differentiates the tool from get_technicals by emphasizing raw vs. calculated data.

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 explicitly instructs when to use this tool versus the sibling: use get_technicals for calculated indicators and only use get_chart when a raw series is needed. This is direct, actionable routing guidance with no ambiguity.

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