flowforge-mcp

flowforge_get_test_run

Read a test run's status and per-iteration results, and retry failed iterations. Poll after starting a run until status is completed or failed to inspect scores and failure reasons.

Instructions

Read a test run's status (and per-iteration results), or retry it.

Poll this after flowforge_run_test until the status is terminal (completed/failed); results include scores and failure reasons.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

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

Input Schema

Name	Required	Description	Default
`params`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Nov 6, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false; the description adds value by disclosing that this same tool can trigger a retry (explaining the non-read-only hint) and that returned results carry scores and failure reasons. It stops short of saying whether retry only re-executes failed iterations by default or what state the run must be in to retry, which the schema covers only partially.

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?

Two short sentences, front-loaded with the primary read purpose and followed immediately by the polling workflow. No filler; every clause carries information the agent needs.

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-shape explanation is unnecessary, and the description correctly focuses on the polling loop and the read-vs-retry split. The remaining gap is retry semantics (default scope of retried iterations, preconditions), which is left to the schema.

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

Parameters3/5

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

The schema's nested GetTestRunInput documents each parameter (retry, run_id, include_results, response_format, retry_iterations), so the schema does most of the work. The description only implies include_results via 'per-iteration results' and says nothing about retry_iterations scope or output format choice, so it adds little beyond the structured 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?

States a specific verb and resource plus its dual mode ('Read a test run's status ... or retry it') and names the producing sibling, flowforge_run_test. An agent can distinguish this from flowforge_run_test and flowforge_list_tests without opening any schema.

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 explicit when-to-use guidance: poll this after flowforge_run_test until the status is terminal (completed/failed). It does not state when not to use it or whether a terminal run can still be retried, but the sequencing guidance is clear and directly actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server