simulate

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

With no annotations, the description fully explains the tool's effect: it emits data that drives synced controls, moving gauges and filling sparklines. It also clarifies it acts 'as if from the service' and is for testing, revealing the simulation nature.

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 define the tool's purpose and use case, followed by clear parameter descriptions. No unnecessary words or repetition.

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 description covers the tool's purpose, use case, and parameters adequately. Since an output schema exists, the absence of return value explanation is acceptable. Minor missing guidance on prerequisites or side effects (e.g., no mention of requiring a connection or channel state).

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%, but the description provides meaningful details: payload_json is described with a concrete example and purpose ('the frame to emit'), and event is explained with its default value. This adds significant value beyond the raw schema types.

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 emits a data frame as if from the service, for live demo/no-backend testing. The verb 'emit' and resource 'data frame onto the channel' are specific, and the purpose is distinct from siblings like set_control_value or say_in_chat.

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 indicates usage for 'live demo / no-backend testing', providing clear context. However, it does not explicitly state when not to use this tool or list alternatives, leaving the guidance slightly implicit.

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