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flexsim_experimenter_status

Check whether a FlexSim Experimenter exists and list its scenarios and job count read-only, helping you inventory experiments before creating or running them.

Instructions

Report Experimenter existence + scenarios read-only (window or Python backend).

SOLO LECTURA (nunca escribe): detecta el Experimenter via Model.find(name)
y/o scan de objetos del modelo por clase conteniendo "Experiment"
(solo model().subnodes + getname(classobject()), sin comandos nuevos).
Lista escenarios como subnodos del Experimenter y cuenta jobs solo si hay
un subnodo visible con "job" en el nombre (si no, jobs=0). NUNCA crea,
conecta ni lanza nada.

Args:
    name: nombre del Experimenter (default Experimenter1).

Returns JSON {exists, name, scenarios, jobs, note}
(+ hint cuando no existe: crearlo a mano en Toolbox).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so thoroughly: it states the tool is strictly read-only, explains the detection mechanism (Model.find and/or class scan of subnodes), and details the job-counting rule (jobs=0 unless a visible subnode contains 'job'). It also explicitly guarantees no creation, connection, or launching occurs.

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

Conciseness3/5

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

The core purpose is front-loaded, but the text is padded with bilingual duplication ('read-only'/'SOLO LECTURA') and repeats the non-mutation guarantee several times ('nunca escribe', 'NUNCA crea, conecta ni lanza nada'). The repetition dilutes rather than strengthens the definition.

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?

An output schema exists so return values need not be re-explained, yet the description still documents the JSON shape {exists, name, scenarios, jobs, note} plus the not-found hint, which is useful for anticipation. Combined with the thorough behavioral detail and parameter meaning, it is complete enough for an agent to call correctly.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate for the single parameter, and it does: 'name' is defined as the Experimenter's name with a stated default of Experimenter1. This matches the schema default and adds clear meaning beyond the bare property definition.

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

Purpose4/5

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

The opening line names a specific verb and resource: report the Experimenter's existence, scenarios and jobs in read-only fashion. It implicitly contrasts with the sibling flexsim_experimenter_run by insisting it never creates/connects/launches. The purpose is unambiguous, though the bilingual restatement adds clutter rather than clarity.

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

Usage Guidelines3/5

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

Usage is only implied: an agent infers this is a pre-flight status/inventory check before running experiments, and the description does give a concrete next step for the not-found case ('crearlo a mano en Toolbox'). But it never explicitly says when to prefer this over flexsim_experimenter_run or flexsim_experiment_plan, leaving routing to inference.

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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