market_recent_candles

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

With no annotations, the description fully discloses behavioral traits: returns 1-minute candles, capped at 12 hours, and mentions the compact toon format option. It adds context beyond the schema, explaining reasoning behind the cap.

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 with no fluff, front-loading the purpose and immediately following with behavioral guidance.

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 simple 3-parameter tool without output schema, the description covers purpose, usage, and key behavioral traits thoroughly. It explains what is returned and the available output format.

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 descriptions already cover each parameter. The tool description adds overall context (e.g., cap reasoning) but does not enhance individual parameter semantics beyond the schema.

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 tool retrieves recent 1-minute candle history for a market, specifying its use for intraday structure, momentum, and pullback analysis. It distinguishes from sibling tools like market_price or market_historical_oi by focusing on high-frequency minute 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 provides explicit usage context: best for short intraday checks and micro-pullback analysis. It explains the 12-hour cap to prevent excessive data fetching, but does not explicitly mention when not to use or name alternative tools for longer timeframes.

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