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by io.testchimp
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List Execution Job Dimension Values

list-execution-job-dimension-values
Read-onlyIdempotent

List distinct execution-job dimension values (platform, device family, OS version, screen resolution, orientation) for filtering get-execution-history. Optional scenarioId, environment, release, timeWindow, branchId, branchName, dimensionFilters, dimension.

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": "list-execution-job-dimension-values"
  }
}

Input Schema

NameRequiredDescriptionDefault
botIdNoQA bots: your botId from your stored TestChimp binding.
releaseNo
branchIdNo
dimensionNo
branchNameNo
scenarioIdNo
timeWindowNo
environmentNo
projectApiKeyNoQA bots: your own project API key from your stored TestChimp binding. Required on every call except get-bot-credentials, get-project-credentials and get-bot-compat. Never print it.
dimensionFiltersNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, so the safety profile is covered. The description adds that values are 'distinct' and mentions optional filters, but it does not add behavioral context such as auth requirements, rate limits, or how filters combine.

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 a single front-loaded sentence followed by a compact list of optional filters. It is appropriately sized and wastes no space.

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 tool with 10 parameters, nested objects, low schema description coverage, and no output schema, the description is too thin. It covers the purpose and names optional filters, but leaves important parameter semantics and filtering behavior unexplained.

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 20%, so the description should compensate with meaningful parameter semantics. It lists eight optional parameter names and expands the dimension enum values in natural language, but it does not explain what timeWindow, dimensionFilters, or the other parameters mean or how they affect results.

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 states a specific verb and resource: 'List distinct execution-job dimension values', enumerates the dimensions, and explicitly links the tool to filtering get-execution-history. This distinguishes it from the sibling get-execution-history, which retrieves history rather than filter values.

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?

It gives clear context that the tool is for filtering get-execution-history, implying it should be used when the agent needs valid filter values. However, it does not explicitly state when not to use it or name alternative tools for discovering dimension values.

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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