Discovery tool: list every pre-built scenario template (id, label, category, description, primary output, documented inputs with defaults/units, and available output metrics), plus how to run a custom free-form scenario and the supported period labels. No required parameters.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full transparency burden. It discloses the output contents and explicitly states 'No required parameters,' while the 'Discovery tool' label implies a safe, read-only operation, which adds meaningful 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 entire description is one well-structured sentence that front-loads the key purpose and packs all essential detail (output fields, extra instructions, parameter note) without waste. Every clause adds value and there is no redundancy.
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 lack of output schema and annotations, the description fully compensates by enumerating the returned fields, noting no required parameters, and even mentioning additional included guidance on custom scenarios and period labels. This gives an agent enough context to invoke and interpret the tool correctly.
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?
The tool has zero parameters and an empty schema with 100% coverage. The description confirms 'No required parameters,' which aligns with the schema and adds no unnecessary detail, earning the baseline 4 for param-less tools.
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 opens with 'Discovery tool: list every pre-built scenario template' which is a specific verb+resource that clearly identifies what the tool does. The listed output fields provide exact detail, and the 'Discovery' label distinguishes it from the sibling execution tools like run_scenario and sensitivity_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 'Discovery tool' label implicitly tells the agent to use this when needing to explore available templates, not for running or analyzing scenarios. While it does not explicitly name alternative tools, the context makes the appropriate use case clear, with no exclusion needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct operation: health_check for status, list_templates for discovery, run_scenario for single simulations, compare_scenarios for multi-scenario comparison, sensitivity_analysis for input sweeping, and break_even for root-finding. There is no meaningful overlap or ambiguity between tool purposes.
All tool names follow a clear snake_case pattern, with most using verb_noun construction (run_scenario, list_templates, compare_scenarios). Even though health_check and break_even are compound nouns, they are consistent in style and clearly action-oriented.
Six tools is well within the ideal range and each tool fills a necessary role for scenario simulation. The set covers running, comparing, sensitivity analysis, break-even solving, discovery, and system health without being bloated or sparse.
The tool surface covers the full lifecycle of scenario analysis: discover templates, run a scenario, compare multiple, vary inputs, and solve for targets. Custom scenarios are also supported via run_scenario, so there are no critical gaps in the domain.