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openl-tablets

OpenL MCP Server

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Delete Table

openl_delete_table
Destructive

Delete an entire table from a project, clearing all its rows and columns so the table no longer exists after recompilation. Use for removing tables completely; for partial removals, use delete rows or columns instead.

Instructions

Delete an ENTIRE table from a project. The whole table area is cleared from the sheet regardless of table type, so the table no longer exists once the project is recompiled. To remove only a row or column WITHIN a table, use openl_delete_table_rows / openl_delete_table_columns instead. If the given id went stale through an edit made via this server, it is resolved to the current id automatically. The studio does not auto-compile after the delete — run openl_project_status afterward to confirm the project still compiles (a dangling reference to the deleted table surfaces there).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableIdYesTable identifier - unique ID assigned by OpenL Studio (e.g., 'calculatePremium_1234'). VOLATILE: derived from the table's location, so it changes when an edit relocates the table (it had no room to grow in place) — use the 'tableId' returned by the latest openl_update_table/openl_append_table response, or refresh via openl_list_tables().
projectIdYesProject ID returned by backend. Use the exact 'projectId' value from openl_list_projects() response without modification or reformatting.
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?

Annotations already indicate destructiveHint=true. Description adds key behavioral details: entire table area is cleared, table no longer exists after recompilation, stale ID resolution, and that the studio does not auto-compile immediately. No contradiction.

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?

Four clear sentences, each adding unique value. Front-loaded with purpose, then scope, alternatives, stale ID handling, and post-step advice. No 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?

Covers key aspects: what it does, scope, alternatives, stale ID, post-delete check. Lacks explicit mention of return value or confirmation, but overall complete for a deletion tool.

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. Description adds marginal value by noting tableId can go stale and auto-resolution, but does not significantly enhance understanding beyond 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?

Description states 'Delete an ENTIRE table from a project' with specific verb and resource. It distinguishes from sibling tools that delete rows/columns by explicitly naming them. The scope is clearly defined.

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

Usage Guidelines5/5

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

Explicitly provides when to use this tool vs alternatives, e.g., 'To remove only a row or column WITHIN a table, use openl_delete_table_rows / openl_delete_table_columns instead.' Also advises to run openl_project_status afterward to check for dangling references.

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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