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openl-tablets

OpenL MCP Server

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List Project Tables

openl_list_tables
Read-onlyIdempotent

List all tables in a project with optional filters by kind, name, or properties. Returns table metadata including tableId for subsequent operations.

Instructions

List all tables/rules in a project with optional filters for type, name, and file. Returns table metadata including 'tableId' (the 'id' field) which is required for calling get_table(), update_table(), append_table(), or run_project_tests(). Use the 'tableId' field from the response to reference specific tables in other API calls. IMPORTANT: a table id is derived from its location and changes when an edit relocates the table (it had no room to grow in place). After openl_update_table/openl_append_table, use the 'tableId' those tools return (or re-run openl_list_tables); an id from a listing taken before such an edit is stale.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoFilter by table kinds (array of strings). Valid values: 'Rules', 'Spreadsheet', 'Datatype', 'Data', 'Test', 'TBasic', 'Column Match', 'Method', 'Run', 'Constants', 'Conditions', 'Actions', 'Returns', 'Environment', 'Properties', 'Other'. Omit to show all kinds.
nameNoFilter by table name fragment (e.g., 'calculate', 'Premium'). Omit to show all tables.
limitNo
offsetNo
projectIdYesProject ID returned by backend. Use the exact 'projectId' value from openl_list_projects() response without modification or reformatting.
propertiesNoFilter by project properties. Properties must be prefixed with 'properties.' in the query string (e.g., properties.state='CA', properties.lob='Auto'). This is handled automatically by the API client.
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
Behavior5/5

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

Adds critical behavioral information beyond annotations: table ID mutability and staleness after updates/append operations. This complements the readOnlyHint (true) by describing the transient nature of output values.

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?

Front-loaded with the core action and resource, then efficiently conveys output usage and a critical warning. No extraneous sentences; every sentence adds value.

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?

Despite no output schema, the description explains the key returned field (tableId) and its role. Could include a full list of returned fields, but the main purpose is clear and the warning about staleness compensates.

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 71%, so the schema already documents most parameters. The description mentions 'type, name, and file' filters but doesn't elaborate on parameter specifics beyond the output usage. Adequate but not exceptional.

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 verb 'List' and resource 'tables/rules in a project' with optional filtering. It distinguishes from sibling tools like openl_get_table (single table) and openl_update_table (modification) by focusing on listing and metadata retrieval.

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?

Provides practical guidance on using the output 'tableId' for subsequent API calls and warns about stale IDs after edits. Lacks explicit exclusions or comparisons to alternatives, but the context is sufficient for typical use.

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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