monte_carlo_simulation

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

Without annotations, the description must fully disclose behavior, but it only states the action. It does not mention whether the tool mutates state, requires specific permissions, or what the output contains (despite an output schema existing). Key behavioral traits like simulation assumptions or performance implications are absent.

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 (one sentence), which is efficient, but it omits essential details that could have been included without verbosity. Front-loading is fine, but the content is too sparse to be fully useful.

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?

Given the tool's complexity (8 parameters, output schema) and the rich sibling context, the description fails to provide enough context. It does not explain what the simulation does with backtest results, how to interpret results, or how it relates to other analysis tools.

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?

With 63% schema coverage, the description adds no parameter-level information. It does not explain how parameters like symbol, strategy, or num_simulations relate to the simulation, nor does it compensate for parameters lacking schema descriptions (e.g., fast_period, slow_period).

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 runs a Monte Carlo simulation on backtest results, using a specific verb ('Run') and resource ('Monte Carlo simulation on backtest results'). It distinguishes from sibling backtesting tools by focusing on simulation rather than backtest execution, though it could be more specific about the inputs and outputs.

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?

No guidance is provided on when to use this tool versus alternatives like backtest_portfolio or walk_forward_analysis. The description does not mention prerequisites (e.g., having prior backtest results) or when not to use it.

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