Plecs Plot

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

No annotations, so the description carries the full burden. It usefully discloses the default TimeSpan (1e-3 s) for waveform runs and that forcing the PLECS renderer errors when unavailable, but says nothing about save_to/overwrite semantics, whether runs mutate the model, or cost/latency.

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 tight sentences with backticked option values, front-loaded with the core action and output. No 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?

With 9 parameters, zero schema descriptions, no annotations, and no output schema, the description should explain the save/inline/overwrite trio and options. As written, an agent can only reliably call it with model_name and defaults.

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% across 9 parameters, yet only kind, renderer, and analysis_name get any explanation. save_to, overwrite, inline, options, and signal_indices are entirely undocumented in both schema and description, so the agent must guess their meaning.

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?

States a specific verb+resource+output: 'Run a simulation/analysis and return a PNG.' The image-returning nature distinguishes it from simulation/analysis siblings like plecs_simulate and plecs_analyze, though the description never says so explicitly.

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?

Gives conditional guidance for parameters (renderer='plecs' errors if unavailable; matplotlib needed for overlays; kind='bode' requires analysis_name), but never states when to pick this tool over plecs_simulate, plecs_analyze, or plecs_capture, which is the key routing decision for an agent.

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