SIMULATE. Solve for the scenario input value required to make an output metric hit a target value (deterministic bisection). Requires 'template', 'solve_for', 'target_value'.
| Name | Required | Description | Default |
|---|---|---|---|
| bounds | No | ||
| inputs | No | ||
| horizon | No | ||
| template | Yes | ||
| solve_for | Yes | ||
| period_label | No | ||
| target_value | Yes | ||
| target_metric | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals the method (deterministic bisection) but does not explain edge cases such as what happens if no solution exists, whether it is a safe read-only operation, or what the return format is. Significant behavioral information is missing for a solver tool.
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 a single, well-structured sentence with a 'SIMULATE' prefix that immediately sets context. It is concise, front-loaded with the core purpose, and includes the essential required parameters without unnecessary verbosity.
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?
The tool is complex (8 parameters, no output schema, no annotations), but the description only covers the core purpose and three parameter names. Missing details on return values, bounds behavior, solution existence, and relationship to sibling tools make it incomplete for an agent to invoke 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?
Schema description coverage is 0%, and the description only lists three required parameter names (template, solve_for, target_value) without explaining their meanings or relationships. Parameters like bounds, inputs, horizon, period_label, and target_metric are entirely unexplained, so the description adds minimal value over the raw schema.
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 action: 'Solve for the scenario input value required to make an output metric hit a target value' using deterministic bisection. This clearly differentiates it from sibling tools like sim_run or sim_sensitivity which likely run or vary simulations. The required parameter names are also explicitly listed.
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 implies usage for break-even analysis (solving for an input to hit a target) but does not explicitly state when to use this tool versus alternatives like sim_run or sim_sensitivity. It mentions required parameters but provides no exclusions or explicit alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clear, distinct purposes across three namespaces (calc_, decide_, sim_) plus composites. Some conceptual overlap exists (e.g., decide_sensitivity vs. sim_sensitivity, decide_score vs. decide), but descriptions clarify the boundaries well.
Names follow a consistent snake_case convention with a namespace prefix (calc_, decide_, sim_) and a descriptive verb_noun structure. Even composite tools and utilities like health_check and list_capabilities fit the pattern.
24 tools is on the heavier side, but it's justified for a meta-server exposing three distinct engines plus cross-domain composites. The count is appropriately scoped for the breadth of capabilities advertised.
The set covers all core domains with discovery (list_capabilities, *_list_*), health_check, and composite tools linking simulation to decision and valuation. Minor gaps include lack of a template management tool, but sim_run accepts free-form models, mitigating this.