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openl-tablets

OpenL MCP Server

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openl List Tables

openl_list_tables
Read-onlyIdempotent

List tables or rules in an OpenL project. Filter by kind, name, or file to retrieve table metadata, including tableId for subsequent API calls.

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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID returned by backend. Use the exact 'projectId' value from openl_list_projects() response without modification or reformatting.
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.
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
limitYes
offsetYes
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint. The description adds value by explaining the output's purpose (tableId for other calls) and doesn't contradict the safe, read-only nature. No destructive behavior hinted.

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?

Three succinct sentences with no wasted words. Purpose is front-loaded, and usage guidance is compact. Ideal length for quick comprehension.

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?

Describes returned tableId and its utility, but lacks explicit mention of pagination (limit, offset) or response structure details like total count or other metadata fields. Given no output schema, more context would be beneficial.

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 71%, so baseline is 3. The description mentions filters by 'type, name, and file', but the schema uses 'kind' and 'properties' instead of 'file', causing slight inconsistency. It adds limited extra meaning beyond 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?

Clearly states the verb 'List' and resource 'tables/rules in a project'. Explicitly mentions the returned 'tableId' and its role in other calls, distinguishing it from sibling tools like openl_get_table or openl_update_table.

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 clear context: use this to list tables and obtain tableId for subsequent operations. Although it doesn't explicitly state when not to use, the linkage to other specific tools implies its role as a prerequisite, giving good directional guidance.

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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