run_monte_carlo

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

Annotations provide minimal behavioral info (readOnlyHint=false, destructiveHint=false). The description adds that it randomly varies component values and runs multiple simulations, but does not disclose side effects (e.g., circuit modifications), time cost, or result storage. It adds some value beyond annotations but could be more specific.

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 concise (3 sentences) and front-loaded with the purpose. The list of parameter explanations is helpful but incomplete. It earns its place without redundancy, but could be restructured to cover all parameters.

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 11 parameters, no output schema, and simple annotations, the description is incomplete. It does not explain how results are returned, the behavior of many parameters, or the overall workflow. A more complete description would include default tolerance handling, seed usage, and frequency/time dependencies.

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 coverage is 0%, so the description must explain parameters. It briefly explains analysis_type and tolerances but ignores 9 of 11 parameters (num_runs, default_tolerance_pct, seed, etc.), leaving the agent with insufficient understanding of how to configure the analysis.

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: running Monte Carlo analysis under component tolerances, with a specific verb ('Run') and resource ('Monte Carlo analysis'), and distinguishes from sibling tools that perform single analysis types (e.g., run_ac_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?

No explicit guidance on when to use this tool vs alternatives like run_worst_case or other statistical tools. The description only lists analysis_type options but does not indicate when Monte Carlo is preferable, nor does it provide exclusions or prerequisites.

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