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Run trade study

run_trade_study
Idempotent

Run an existing declared trade study over at most 256 design points and return objective values and the Pareto front. Paid. Call it directly: it charges what the job uses, never more than its estimated maximum or the max_spend_credits you set. request_id is optional; set one to make a retry safe. Returns job_id immediately. Poll get_job_status for later progress.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "run_trade_study"
  }
}

Input Schema

NameRequiredDescriptionDefault
rowsNoOnly for cost_mode "agent_authored" on generate_safety_analysis: {conditions:[{target,description,severity,...}],modes:[{target,mode,severity,occurrence,detection,...}]}; with analysis "stpa": {losses:[{id,description}],hazards:[{id,description,losses}],controllers:[{target,processModel}],controlActions:[{from,to,name,ucas:[{id,type,context,contextVariables,hazards,constraint}|{type,notApplicable,rationale}]}],feedback:[{from,to,name,updates}],constraints:[{id,name,text}]}.
modelNo
studyNo
eventsNo
formatNo
promptNo
stop_sNo
analysisNoFor generate_safety_analysis: fha, fmea, both (default) or stpa. stpa needs no standard.
fidelityNo
model_idNoA model from a generation job (model_ id) or a saved studio model (m_ id); a saved model is read at the head of main.
providerNo
standardNo
cost_modeNomanaged
max_depthNoOnly for run_agent_swarm: levels of division, 1 to 3 (default 2). At 2 and 3, a subsystem the orchestrator judges too large for one agent is divided again inside its frozen boundary.
subsystemNoFor reprompt_agent: qualified name of the subsystem, e.g. "Rover::DriveUnit". For run_agent_swarm on a saved model: the subsystem to decompose one level further (its parts get the agents); leave it out to work on the whole system's subsystems.
request_idNo
scenario_idNo
simulationsNo
specificationNoOnly for cost_mode "agent_authored" on generate_system_model and build_full_system; see those tools for its schema.
simulation_typeNo
max_spend_creditsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / analysis / description
      Added value: +"For generate_safety_analysis: fha, fmea, both (default) or stpa. stpa needs no standard."
    • changedInput schema / properties / analysis / enum
      Previous value: -[
      -  "fha",
      -  "fmea",
      -  "both"
      -]New value: +[
      +  "fha",
      +  "fmea",
      +  "both",
      +  "stpa"
      +]
    • changedInput schema / properties / rows / description
      Previous value: -"Only for cost_mode \"agent_authored\" on generate_safety_analysis: {conditions:[{target,description,severity,...}],modes:[{target,mode,severity,occurrence,detection,...}]}."New value: +"Only for cost_mode \"agent_authored\" on generate_safety_analysis: {conditions:[{target,description,severity,...}],modes:[{target,mode,severity,occurrence,detection,...}]}; with analysis \"stpa\": {losses:[{id,description}],hazards:[{id,description,losses}],controllers:[{target,processModel}],controlActions:[{from,to,name,ucas:[{id,type,context,contextVariables,hazards,constraint}|{type,notApplicable,rationale}]}],feedback:[{from,to,name,updates}],constraints:[{id,name,text}]}."
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Goes well beyond the annotations by disclosing cost semantics (charges actual usage, never above the estimate or max_spend_credits) and the asynchronous contract (returns job_id immediately, poll get_job_status). It also qualifies the idempotentHint=true by noting retry safety requires setting request_id, which is useful nuance rather than a contradiction.

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?

Five short sentences, front-loaded with the action and scope, then cost, then retry, then polling. Every sentence carries information; only the 'Paid' fragment and 'Call it directly' are slightly clipped in a way that could read as phrasing rather than detail.

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

Completeness2/5

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

For a 21-parameter, no-output-schema, async, paid job tool, the description covers cost and job lifecycle but not the parameter families that determine what actually runs. An agent still has no narrative account of how study/model/format/simulations relate, which is a substantial gap on a tool this complex.

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

Parameters2/5

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

Schema description coverage is only 29% across 21 parameters, so the description must compensate and largely does not. It adds real meaning for max_spend_credits (the spend ceiling) and request_id (optional but makes retries safe), yet leaves the bulk of the surface — format, analysis, simulations/events, model, study, fidelity, provider — entirely to the bare schema.

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?

States a specific verb and resource ('run an existing declared trade study') plus scope ('at most 256 design points') and the return ('objective values and the Pareto front'). No sibling tool performs trade studies, so an agent can distinguish it immediately from run_simulation or the mbe_* family.

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?

Gives concrete operational guidance: call it directly, cost is metered and capped, set request_id when a retry may follow, and poll get_job_status afterward. It stops short of saying when to prefer this over estimate_cost or run_simulation, and never says what preconditions 'existing declared' implies.

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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