analytics_monte_carlo_simulation

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Run' implies execution, the description doesn't mention whether this is a read-only analysis or creates/modifies data, what permissions might be required, whether it's computationally intensive, what the output format is, or any error conditions. For a complex simulation tool with no annotation coverage, this is a significant gap in behavioral context.

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 - a single sentence that efficiently communicates the core purpose. Every word earns its place: 'Run' (action), 'Monte Carlo simulation' (method), 'for risk analysis and scenario planning' (application). There's no wasted verbiage or redundant information.

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?

For a complex simulation tool with 6 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns, how results are presented, whether it creates persistent outputs, or what computational resources are required. The description covers only the basic purpose, leaving critical contextual gaps for proper tool selection and invocation.

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 67%, so the schema documents most parameters well. The description adds no parameter-specific information beyond what's in the schema - it doesn't explain the relationship between 'formula' and 'variables', provide examples of valid formulas, or clarify distribution parameter usage. With moderate schema coverage, the baseline of 3 is appropriate as the description doesn't compensate for the coverage gap but doesn't contradict the schema either.

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 purpose: 'Run Monte Carlo simulation for risk analysis and scenario planning.' It specifies the verb ('Run') and resource ('Monte Carlo simulation'), and distinguishes from many siblings by focusing on simulation rather than forecasting, valuation, or dashboard creation. However, it doesn't explicitly differentiate from 'analytics_scenario_comparison' or 'analytics_sensitivity_analysis' which might also involve scenario analysis.

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 no guidance on when to use this tool versus alternatives. With numerous sibling tools like 'analytics_scenario_comparison', 'analytics_sensitivity_analysis', and various forecasting tools, there's no indication of when Monte Carlo simulation is preferred over other analytical methods. The description only states what it does, not when it's appropriate.

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