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openl-tablets

OpenL MCP Server

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Start Project Tests

openl_start_project_tests
Idempotent

Starts project test execution. Automatically opens closed design projects; for local repos, runs tests directly. 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
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.
projectIdYesProject ID returned by backend. Use the exact 'projectId' value from openl_list_projects() response without modification or reformatting.
fromModuleNoModule name to run tests from (reserved for future use - not currently used)
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.
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
Behavior3/5

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

The description adds behavioral context beyond annotations (auto-open for design repos, not for local), but does not disclose potential side effects or details about execution status/metadata. Annotations provide safety hints but description could be more thorough.

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-loading the purpose, then adding context and follow-up tools. No wasted words or redundancy.

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?

Given no output schema, the description mentions returns execution status and metadata, but could be more specific about the return structure. However, it effectively complements the schema and points to result retrieval tools, making it fairly complete.

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 coverage is 100% with detailed parameter descriptions. The tool description does not add significant meaning to parameters beyond what the schema already provides, so baseline score of 3 is appropriate.

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 tool starts project test execution and distinguishes behavior for design repositories vs local repo. It also mentions that results can be retrieved with specific sibling tools, but does not explicitly differentiate from other execution tools like openl_start_trace.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context about automatic project opening for design repos and directs users to result retrieval tools, but lacks explicit guidance on when not to use this tool vs alternatives (e.g., if project must be open or if running tests differently).

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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