Evolution Discover Patterns

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

Annotations declare a non-read-only, non-idempotent, closed-world operation, and the description usefully adds that generation is LLM-driven with an associated temperature concept. However, it does not disclose what side effects occur (are patterns persisted?), that repeat calls yield different results, or any latency/cost implications of the LLM call.

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 purpose, then method, then follow-on step. Minor redundancy between 'using LLM analysis' and 'Uses Claude,' but no filler.

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?

With an output schema present, return values need not be described, and the schema fully covers parameters. The description conveys purpose, method, and the downstream backtest step, leaving only small gaps around persistence and non-determinism.

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 five parameters (symbol, days, count, timeframe, temperature) are already documented with defaults and examples. The description mentions OHLCV and entry/exit conditions but adds no syntax or constraint detail beyond the schema, so the baseline applies.

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 and resource ('Discover trading patterns') plus the method ('LLM analysis', 'Uses Claude'). It implicitly separates itself from siblings by noting patterns 'can be backtested afterward' (vs. evolution_run_backtest) and that it consumes OHLCV data (vs. evolution_fetch_market_data). The boundary against evolution_evolve_strategy is not spelled out, so it stops short of a 5.

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 sketches the workflow ('generate candidate patterns... backtested afterward') but never states when to choose this tool over evolution_evolve_strategy or validate_strategy, and gives no prerequisites or exclusions. Usage is implied rather than directed.

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