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set_layout_lights

Turn every JMRI layout light (depot, street, signal) on or off in one call. Server-side looping; a failed light does not halt the operation.

Instructions

Turn EVERY layout light ON or OFF at once (depot, street, signal lamps — JMRI Light objects).

Args: turn_on: True to turn every layout light ON, False to turn every layout light OFF.

These are JMRI light objects wired to the layout/scenery itself — NOT a locomotive's own headlight/cabin/rear-light functions. Call for a lighting request that does NOT name a locomotive ("turn on all the lights", "éteins toutes les lumières" with no loco mentioned). If the request DOES name a locomotive ("all of the Autorail's lights"), use set_loco_lights or set_all_locos_lights instead — never this tool for that case.

Never loop set_light yourself for "every light"/"toutes les lumières" — this loops server-side in one call over every light JMRI reports.

Returns {"succeeded": [...], "failed": [...]}, each entry shaped like set_light's own return value plus "name". One light failing doesn't stop the rest (catch-and-continue).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
turn_onYes
Behavior4/5

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

Describes that it loops server-side, returns success/failure lists, and catch-and-continue behavior. No annotations provided, so description carries full burden. Could mention potential side effects (e.g., lights are changed), but overall transparent.

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

Conciseness5/5

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

Front-loaded with purpose, then args, then context, then return value. Every sentence adds value; no redundancy.

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?

Covers purpose, usage, behavior, and return format. Could mention if any lights are not controllable, but completeness is high for a simple boolean tool.

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?

Only parameter turn_on is fully explained: 'True to turn every layout light ON, False to turn every layout light OFF.' Schema coverage is 0%, so description compensates completely.

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?

Clearly states 'Turn EVERY layout light ON or OFF at once (depot, street, signal lamps — JMRI Light objects)'. Specific verb-resource-scope combination, and distinguishes from sibling tools like set_loco_lights and set_all_locos_lights.

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

Usage Guidelines5/5

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

Explicitly says when to use (lighting request not naming a locomotive) and when not to (if request names a locomotive, use set_loco_lights or set_all_locos_lights). Also advises against using set_light in a loop.

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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