DECIDE. Test how robust the decision winner is to changes in CRITERIA WEIGHTS (distinct from sim_sensitivity, which varies scenario inputs). Sweeps each weight +/-variation and reports a robustness score + flip points.
| Name | Required | Description | Default |
|---|---|---|---|
| steps | No | ||
| method | No | ||
| scores | Yes | ||
| options | Yes | ||
| criteria | Yes | ||
| variation | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosure. It transparently describes the sweep behavior ('Sweeps each weight +/- variation') and the outputs ('robustness score + flip points'), which is valuable behavioral context beyond the tool name. It does not mention side effects, but as a sensitivity analysis tool, it implies a read-only computation.
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 extremely concise, using only two sentences to convey purpose, distinction from a sibling, the sweep method, and outputs. Every sentence earns its place, and the 'DECIDE.' prefix is a meaningful category marker rather than filler.
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 tool's complexity (6 parameters, nested objects, no output schema, no annotations), the description is reasonably helpful but not fully complete. It explains the core behavior and output, but does not clarify parameter meanings for 'method' and 'steps', nor the expected shape of the 'scores' object. This is adequate for basic invocation but leaves gaps for precise use.
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 coverage is 0%, so the description must compensate for missing parameter details. It adds meaning for 'variation' and 'criteria' by explaining that weights are swept +/- 'variation'. However, it does not explain the semantics of 'method', 'steps', or the structure of 'scores', leaving some parameter ambiguity.
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 a specific verb ('Test') and resource ('decision winner') with a precise focus on changes in criteria weights. It explicitly distinguishes itself from sim_sensitivity by contrasting weight variation vs. scenario inputs, making the tool's unique purpose unambiguous.
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 explicitly names the sibling tool sim_sensitivity and explains the distinction: this tool varies criteria weights, while sim_sensitivity varies scenario inputs. This gives clear guidance on when to use this tool versus an alternative.
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.