Skip to main content
Glama
openl-tablets

OpenL MCP Server

Official

openl Start Project Tests

openl_start_project_tests
Idempotent

Initiate test execution for a project; automatically opens design repositories if closed. Optionally specify a table ID or test ranges to run only specific tests. Returns execution status and metadata.

Instructions

Start project test execution. For design repositories the project is automatically opened if closed; for repository 'local' the project is not opened (tests run directly). Returns execution status and metadata. Test results can be retrieved using openl_get_test_results_summary, openl_get_test_results, or openl_get_test_results_by_table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID returned by backend. Use the exact 'projectId' value from openl_list_projects() response without modification or reformatting.
tableIdNoTable ID to run tests for a specific table. Table type can be test table or any other table. If not provided, tests for all test tables in the project will be run.
testRangesNoTest ranges to run. Can be provided only if tableId is Test table. Example: '1-3,5' to run tests with numbers 1,2,3 and 5. If not provided, all tests in the test table will be run.
fromModuleNoModule name to run tests from (reserved for future use - not currently used)
response_formatNoResponse format: 'json' for structured data, 'markdown' for human-readable (default), 'markdown_concise' for brief summary (1-2 paragraphs), 'markdown_detailed' for full details with contextmarkdown
Behavior4/5

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

The description adds behavioral details beyond annotations, such as auto-opening projects for design repos and not for local repos. Annotations indicate idempotent and open-world hints, which are consistent.

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 concise with three sentences, front-loaded with the main action, and no unnecessary information.

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?

While there is no output schema, the description mentions return of status and metadata and points to result retrieval tools. It covers the main behaviors and parameter usage adequately.

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?

Schema coverage is 100%, and the description adds value for projectId by specifying to use the exact value from openl_list_projects. Other parameters are well-described in the 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?

The description clearly states the tool starts test execution and distinguishes behavior for design vs local repositories. It also directs to sibling tools for retrieving results, avoiding confusion.

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?

The description provides context on when to use the tool and mentions alternatives for retrieving results. However, it does not explicitly state when not to use this tool compared to other test-related siblings.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/openl-tablets/openl-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server