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set_component_suppression

Change a component's load state in an active assembly to manage configuration variants or improve performance by using suppressed or lightweight states.

Instructions

Cambiar el estado de carga de un componente en el ensamble activo.

Uso típico autopartes: suprimir/resolver componentes para crear variantes de configuración (con/sin opcionales), o aligerar grandes ensambles con cientos de tornillería usando estado "lightweight". [en: Set a component's load state in the active assembly. Typical use: suppress/resolve to build configuration variants, or use 'lightweight' on big assemblies with hundreds of fasteners.]

Args: component_name: SW component instance name from get_active_assembly_info. state: One of "suppressed" (hidden, excluded from BOM, not loaded), "resolved" (fully loaded, default), or "lightweight" (graphics only — saves memory in large assemblies, common in autoparts sub-assemblies with 100+ fasteners). config_scope: "this" (active config only — fast), "all" (apply to every configuration in the document), "specific" (apply to configs listed in config_names). config_names: List of configuration names; required when config_scope="specific". Example: ["Sport", "Premium"] to suppress in those trim variants only.

Returns the component's updated state for the active configuration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNoresolved
config_namesNo
config_scopeNothis
component_nameYes
Behavior4/5

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

The description explains the effects of each state (suppressed: hidden, excluded from BOM; resolved: fully loaded; lightweight: graphics only) and config_scope options. With no annotations provided, this adds essential behavioral context. It does not mention prerequisites (e.g., active assembly) or side effects (e.g., performance implications), but overall it is transparent enough for an AI agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is somewhat verbose due to bilingual content (Spanish followed by English), but the English portion is well-structured with a clear purpose, usage, and parameter list. It is front-loaded with the core action. The bilingual redundancy could be trimmed for conciseness, but it remains functional.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 parameters, no annotations, and no output schema, the description covers the states, scopes, and return value adequately. It lacks error handling or edge-case details, but the provided information is sufficient for typical use cases. The description is complete enough for an AI agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so the description must compensate. It does so excellently by detailing each parameter: component_name source, state options with definitions, config_scope options, and config_names requirement with examples. This provides far more value than the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verb and resource: 'Cambiar el estado de carga de un componente' / 'Set a component's load state'. It provides concrete use cases (configuration variants, lightweight for large assemblies), making the tool's intent unambiguous and distinguishing it from siblings like set_components_suppression and set_mate_suppression.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes typical usage scenarios: suppress/resolve for variants and lightweight for performance. This gives clear guidance on when to use the tool. However, it does not explicitly exclude cases where it should not be used or mention alternatives (e.g., set_components_suppression for batch operations), leaving some ambiguity.

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

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