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OpenL MCP Server

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Get Test Results Summary

openl_get_test_results_summary

Retrieve concise test execution summaries with key statistics—execution time, total tests, passed, and failed—for a project. Get a high-level view of results without examining individual test cases.

Instructions

Get brief test execution summary without detailed test cases. Returns aggregated statistics (execution time, total tests, passed, failed) without the testCases array. Use openl_start_project_tests() first to start test execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unpagedNoReturn all results without pagination
failuresNoNumber of failed test units to include in the summary (default: 5, min: 1)
projectIdYesProject ID returned by backend. Use the exact 'projectId' value from openl_list_projects() response without modification or reformatting.
failuresOnlyNoInclude only failed tests.
response_formatNoResponse format: 'json' for structured, round-trippable data (default), 'markdown' for human-readable output, 'markdown_concise' for a brief summary (1-2 paragraphs), or 'markdown_detailed' for full details with contextjson

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changedv1.2.0
    • addedInput schema / properties / failuresOnly
      Added value: +{
      +  "description": "Include only failed tests.",
      +  "type": "boolean"
      +}
    • changedInput schema / properties / response_format / default
      Previous value: -"markdown"New value: +"json"
    • changedInput schema / properties / response_format / description
      Previous value: -"Response format: 'json' for structured data, 'markdown' for human-readable (default), 'markdown_concise' for brief summary (1-2 paragraphs), 'markdown_detailed' for full details with context"New value: +"Response format: 'json' for structured, round-trippable data (default), 'markdown' for human-readable output, 'markdown_concise' for a brief summary (1-2 paragraphs), or 'markdown_detailed' for full details with context"
  2. Changed1 schema field changedv1.1.0
    • changedInput schema / required
      Previous value: -[
      -  "projectId",
      -  "failures",
      -  "unpaged"
      -]New value: +[
      +  "projectId"
      +]
  3. First observedv0.0.0

TDQS

A3.9/5.0
Behavior4/5

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

The description discloses the key behavioral trait: it returns only aggregated statistics and deliberately omits the testCases array. It also surfaces the dependency on a prior test-start call. With only openWorldHint in annotations, this adds meaningful context beyond the structured data.

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 two sentences with no filler. It front-loads the purpose and return content, then gives the essential prerequisite. It avoids repeating schema details.

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

Completeness3/5

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

With no output schema, the description covers the core return fields but leaves behavior for response_format variants, pagination, and failuresOnly implicit. It also does not state what happens if test execution has not been started, beyond the prerequisite instruction.

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?

Schema description coverage is 100%, so the schema already documents all parameters including projectId, failures, failuresOnly, unpaged, and response_format. The description adds no parameter-level meaning beyond the schema, so it meets the baseline but does not go further.

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 description clearly states the action and resource: getting a brief summary of test execution, and explicitly notes that detailed testCases are excluded. It differentiates itself from the detailed test-results siblings by what it omits, though it does not name the specific sibling tool to use for detailed results.

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 provides a clear, important prerequisite by instructing the agent to call openl_start_project_tests() first. However, it does not explicitly state when to choose this tool over openl_get_test_results or openl_get_test_results_by_table, leaving that differentiation implied rather than stated.

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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