Evolution Fetch Market Data

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

Annotations declare readOnlyHint=false but idempotentHint=true and destructiveHint=false, so the safety profile is already largely covered by structured data. The description adds that data comes from Binance (an external/open-world source) and that it supports backtesting and pattern discovery, which complements the openWorldHint. No contradiction, but the description doesn't resolve the apparent readOnly=false vs. non-destructive nature on its own.

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?

Three short sentences, front-loaded with the core action and source. Slightly split between two sentences that could merge, but no filler or redundancy.

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?

An output schema exists, so return values don't need explanation. Description covers purpose, external source, and pipeline ordering. Could be complete except that it doesn't clarify the readOnly=false annotation implication (why a fetch isn't read-only), a minor gap given rich schema and output schema.

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 symbol, timeframe, and days are all documented in the schema with examples and defaults. The description adds no parameter-specific syntax or format information beyond what the schema already carries. Baseline 3 is correct.

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?

States a specific verb (Fetch), resource (OHLCV market data), and source (Binance), plus the purpose (evolution analysis). Distinguished from siblings discover_patterns and run_backtest by explicitly noting this is the data-acquisition predecessor.

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?

Explicitly says to use this 'before discover_patterns or run_backtest to get data', giving clear ordering context. No exclusion conditions, but the sequencing guidance is unambiguous for the pipeline.

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