simulation_state

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly declares read-only behavior ('Does not mutate the MD scene') and states what is not exposed (physical convergence/collision judgments), which is valuable context beyond the name. It lacks details on return format or performance, but the explicit non-mutation and scope limitations are strong.

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 concise sentences with no filler. It front-loads the main purpose (counts) and then clarifies limitations and side effects. Every sentence adds essential information, making it highly efficient.

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 zero parameters and no output schema, the description covers the core: what it does and what it doesn't do. It is sufficient for an agent to call it safely. Missing details like return format or exact structure could be considered, but for such a simple tool, the description is nearly complete. A small deduction for not suggesting alternatives or noting any assumptions.

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, so the schema provides no semantic content. The description compensates by specifying the exact type of information returned (native quality, pattern and mesh counts) and what it does not include (physical convergence/collision judgments), which adds meaning to the empty schema. With no parameters, a baseline of 4 is appropriate.

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 specifies that the tool reports quality, pattern, and mesh counts, and states what it explicitly does not expose (physical convergence/collision judgments). This distinguishes it from siblings like get_simulation_metrics and simulate by focusing on count-level information. However, it does not name the sibling alternatives explicitly, so it slightly misses the top score.

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 when to use this tool: when you need native counts and verify that the operation is read-only. It clearly states it does not expose physical convergence/collision judgments and does not mutate the scene, which helps an agent decide to use it for safe state inspection. However, it does not explicitly say 'use X instead for physical metrics', so it is not a perfect 5.

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