anylogic_create_model_ple

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

No annotations provided, so the description carries full burden. It discloses PLE restrictions (max agent types, blocks, dynamic agents) but omits success/failure behavior, return values, side effects, or error handling.

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?

Two concise sentences: first states purpose and PLE compliance, second details restrictions and usage. No redundant information, front-loaded with key action.

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?

With no output schema and complex nested parameters, the description covers creation purpose and constraints but lacks return value details, error scenarios, or post-creation steps. Adequate for basic use but not fully complete for an AI agent.

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 100%, baseline is 3. The description adds value by explaining PLE limits and validation context not present in schema, such as max 10 agent types and auto-simplify behavior, improving parameter understanding.

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 creates an AnyLogic simulation model complying with PLE limits. It distinguishes from sibling tools like download, validate, get limits, and upload.

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 says 'Use this to create models that can be downloaded and run in free AnyLogic PLE,' indicating appropriate context. It does not explicitly exclude cases or name alternatives, but the context signals provide clear sibling tool differentiation.

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