SIMULATE. Run 2-3 scenarios and compare their key_results side by side with deltas vs the first (baseline). Optional 'compare_metric' + 'goal' (max|min) picks a winner.
| Name | Required | Description | Default |
|---|---|---|---|
| goal | No | ||
| horizon | No | ||
| scenarios | Yes | ||
| compare_metric | No | ||
| include_projections | 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 does explain the output style ('side by side with deltas vs the first') and the winner selection logic ('compare_metric + goal (max|min) picks a winner'). However, it does not mention whether the tool is read-only, what happens with invalid scenarios, or any edge-case behavior. This is adequate but not comprehensive.
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 two sentences, front-loaded with 'SIMULATE' for immediate context, and every word earns its place. It efficiently conveys the core action, comparison method, and optional winner selection without fluff or 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 absence of an output schema, the description should explain return values, but it only says 'key_results side by side with deltas' without specifying structure or data types. It also fails to explain the effect of 'horizon' and 'include_projections', which are likely important for simulation scenarios. With many sibling tools (sim_run, sim_sensitivity, etc.), more contextual guidance would be needed to integrate this tool effectively.
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%, so the description must compensate for parameter meaning. It only clarifies 'compare_metric' and 'goal' (e.g., 'goal (max|min) picks a winner'). The required 'scenarios' parameter is only hinted at via 'Run 2-3 scenarios', but no format is given. 'horizon' and 'include_projections' are entirely unmentioned, leaving them unclear. This is insufficient for a 5-parameter tool.
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: 'Run 2-3 scenarios and compare their key_results side by side with deltas vs the first (baseline)'. This is a specific verb+resource combination that distinguishes it from sibling tools like sim_run (which likely runs a single scenario) and sim_sensitivity (which analyzes sensitivity). The optional 'compare_metric' and 'goal' for picking a winner further clarifies its unique functionality.
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 scenario comparison ('Run 2-3 scenarios and compare'), but it does not explicitly mention when to use this tool versus alternatives or when not to use it. For example, it does not state that for more than 3 scenarios one should use a different tool, or that sim_compare is preferred over sim_run when side-by-side comparison is needed. The context is clear but lacks explicit exclusions or alternative 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.