sim_sensitivity

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. 'SIMULATE' implies a non-mutating analysis, but it doesn't explain whether it creates resources, requires authentication, modifies state, or how variations are applied. Minimal 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 very short and front-loaded. However, 'SIMULATE.' is a filler word that repeats the tool's domain and adds no information; the second sentence alone would be sufficient. Still, no wasted length beyond that.

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?

This is a nine-parameter sensitivity tool with no output schema and no annotations. The description omits how variations are applied, what the output shape looks like, prerequisites like the required template, and relationships among parameters. It is incomplete for reliable agent 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?

With 0% schema description coverage, the description must explain the many parameters. It only hints at 'scenario inputs' and 'target metric', leaving template, variables, variation, steps, horizon, and period_label unexplained. It does not compensate for the schema gap.

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 identifies a sensitivity-analysis tool: vary scenario inputs to see impact on a target metric. It distinguishes from siblings like sim_run or sim_compare by emphasizing input variation and impact measurement, though it doesn't explicitly name alternatives.

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 when-to-use guidance or alternatives are provided. The phrase 'Vary scenario inputs...' implicitly suggests sensitivity analysis, but it doesn't state when to prefer this over sim_run, sim_compare, or sim_break_even.

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