run_monte_carlo

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

Adds behavioral information beyond annotations: long-running, progress reporting, execution timeout. Annotations indicate non-readOnly and non-destructive, which the description complements without contradiction.

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?

Concise, front-loaded purpose, then prerequisite, defaults, output, and behavioral notes. No extraneous words; each sentence adds value.

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?

Covers purpose, prerequisites, parameters, output metrics, and runtime behavior. With an output schema existing, the description provides sufficient context for the agent to understand and use the tool.

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?

Compensates for 0% schema description coverage by explaining result_id as strategy_id/run_id and simulations defaulting to 1000. This fully clarifies both parameters.

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?

Clearly states the tool runs a Monte Carlo simulation from a saved backtest result, resamples trades, and provides risk metrics. Distinguishes from siblings like run_backtest and run_optimize by requiring their saved output.

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 specifies prerequisite (saved result from run_backtest/run_optimize) and default simulation count. Does not mention exclusions or alternatives but provides clear context for appropriate use.

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