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carmaker-mcp

carmaker-mcp

by dimitr-io
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Wait for a parameter study

cm_study_wait
Read-only

Waits up to a timeout for a CarMaker study run to finish or the study to end, returning only rows not returned by earlier calls. Call again while the study is running to poll progress.

Instructions

Wait until another run of the study has finished or the study has ended, at most timeout_s, and return the rows no earlier call returned (cm_study_status has the whole table and rank_by). Call it again while state is 'running'. Use this for studies instead of cm_wait_end.

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": "cm_study_wait"
  }
}

Input Schema

NameRequiredDescriptionDefault
studyNoStudy id (default: the latest)
detailNobrief: per run label, valid, end status, sector or split times, abort reason. compact: also time, distance, result file and min / max / mean / last of the quantities. full: also every run's keys, workspace values and all statisticsbrief
timeout_sNoLongest time to wait in s, at most 50 (larger values are cut to 50); call again if not finished
until_doneNoReturn only when the study has ended (or at timeout_s)

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.3.0
    • addedInput schema / properties / detail
      Added value: +{
+  "default": "brief",
+  "description": "brief: per run label, valid, end status, sector or split times, abort reason. compact: also time, distance, result file and min / max / mean / last of the quantities. full: also every run's keys, workspace values and all statistics",
+  "enum": [
+    "brief",
+    "compact",
+    "full"
+  ],
+  "type": "string"
+}
    • changedInput schema / properties / timeout_s / description
      Previous value: -"Longest time to wait in seconds; keep it below your client's tool time-out and call again if not finished"New value: +"Longest time to wait in s, at most 50 (larger values are cut to 50); call again if not finished"
    • addedInput schema / properties / until_done
      Added value: +{
+  "default": false,
+  "description": "Return only when the study has ended (or at timeout_s)",
+  "type": "boolean"
+}
  2. Addedv0.2.0

TDQS

A4.7/5.0
Behavior4/5

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

While annotations cover safety (`readOnlyHint: true`), the description adds essential operational context. Specifically, it discloses the filtering behavior ('return the rows no earlier call returned') and the required polling behavior ('Call it again while state is 'running'').

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?

The description is extremely dense and efficient. It front-loads the core functionality, provides necessary constraints, and directs the user to alternatives within one compact paragraph without unnecessary jargon.

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

Completeness5/5

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

Given the detailed input schema (including enum explanations) and clear behavioral requirements, the description provides everything necessary for an AI agent to select and invoke this tool correctly in nearly every context.

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?

Although schema coverage is 100% (baseline 3), the description adds significant semantic value by defining the complexity of the 'detail' enum (brief, compact, full) and explaining the pagination/offset logic of the return value, which goes beyond just naming the fields.

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 defines the function: waiting for a study to finish or end. It uses a specific verb ('Wait') and explicitly ties it to the 'study' resource. Crucially, it provides direct differentiators against the sibling cm_wait_end.

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?

The usage guidelines are exceptional as they specify when to use this tool (waiting for a study run) and when *not* to use it (referencing cm_wait_end). It even provides operational guidance: 'Call it again while state is 'running''.

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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