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

The description clearly discloses that it is '100% deterministic (40-digit decimal math)' and details every major output element: period-by-period projections, key_results, assumptions with defaults filled in, methodology, notes, and a plain-language explanation. This is especially valuable because no annotations are provided, fully compensating for the absence of structured transparency.

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 five sentences, front-loaded with 'Main simulation tool' and proceeding logically through what it runs, what it returns, how to call it, and its deterministic nature. The template list is long but necessary for discoverability; no sentence is redundant.

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?

Despite lacking an output schema and annotations, the description covers all key aspects: it lists return values, supports both template and custom scenarios, explains deterministic behavior, and works in tandem with the rich input schema. This is sufficient for an agent to know when and how to use the tool and what to expect.

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 100% schema coverage, the baseline is 3, and the description adds a useful high-level abstraction: it clarifies the two modes (pre-built template vs free-form 'metrics') and gives the core call pattern ('template + inputs'). This goes slightly beyond the schema by synthesizing which parameters work together, aiding correct invocation.

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 states a specific verb ('Run') and resource ('simulation tool'), and goes beyond by naming both pre-built templates and a free-form 'metrics' model. The phrase 'Main simulation tool' establishes its role relative to siblings like sensitivity_analysis and compare_scenarios, making the purpose unmistakable.

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?

Provides explicit usage instructions: 'Pass template + inputs, plus optional horizon and period_label' and enumerates valid template IDs. However, it does not explicitly explain when to choose this tool over alternatives like break_even or sensitivity_analysis, leaving some inference up to the agent.

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