evolution_fetch_market_data

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

Annotations already cover safety profile: idempotentHint=true and destructiveHint=false. The description adds that data is sourced from Binance and that it downloads historical bars, which provides useful context. However, it does not disclose any side effects (e.g., whether data is stored locally) despite readOnlyHint=false, nor does it mention rate limits or data freshness. The annotation prevents a lower score, but the description itself could be richer.

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 extremely concise and front-loaded. Two sentences convey the core purpose and usage instruction with no wasted words. Every sentence earns its place, and the structure is 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?

The tool is simple and the description, combined with the schema and annotations, gives a clear picture of how to use it. However, a small gap remains: the description does not clarify how the fetched data is made available to downstream tools (e.g., whether it is stored, cached, or returned directly), especially given readOnlyHint=false. With an output schema present, return values are covered, but the side-effect behavior is somewhat ambiguous.

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 provides 100% coverage of parameters, each with clear descriptions and defaults. The description adds no parameter-specific details beyond the schema, so it does not increase understanding beyond what is already structured. Baseline 3 is appropriate given high schema coverage.

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's function with a specific verb and resource: "Fetch OHLCV market data from Binance for evolution analysis." It also mentions downloading historical price bars for backtesting and pattern discovery, which distinguishes it from sibling tools like discover_patterns and run_backtest that operate on the 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 guidance: "Use this before discover_patterns or run_backtest to get data." This names specific downstream tools and clarifies when this tool should be invoked. However, it does not mention alternative data sources or when not to use it, so it stops short of a full when/when-not/alternatives distinction.

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