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openl-tablets

OpenL MCP Server

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Delete Table Rows (raw)

openl_delete_table_rows
Destructive

Remove rows from a table's raw source starting at a specified position; rows below shift up while the header remains intact. Use the returned current table ID for subsequent operations.

Instructions

Delete ONE OR MORE rows starting at 'position' (1..height-1) from a table's raw source, shifting the rows below up. 'count' defaults to 1. The header row (0) cannot be deleted. Operates on the table's RAW source, so it works for any table type. Positions are 0-based (row 0 is the header row, column 0 carries the leading labels). An edit that relocates the table (it had no room to grow in place) CHANGES its location-derived id; the response always returns the table's CURRENT id as 'tableId' (plus previousTableId when it changed) — use it for subsequent calls. Note: the studio does not auto-compile after an edit; this tool reads the table back to trigger the recompile, so a subsequent openl_project_status reflects the change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of rows to delete starting at 'position' (default 1).
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().
positionYes0-based index of the first body row to delete (1..height-1). The header row (0) cannot be deleted. Rows below the deleted block shift up.
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, round-trippable data (default), 'markdown' for human-readable output, 'markdown_concise' for a brief summary (1-2 paragraphs), or 'markdown_detailed' for full details with contextjson

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changedv1.2.0
    • changedInput schema / properties / response_format / default
      Previous value: -"markdown"New value: +"json"
    • changedInput schema / properties / response_format / description
      Previous value: -"Response format: 'json' for structured data, 'markdown' for human-readable (default), 'markdown_concise' for brief summary (1-2 paragraphs), 'markdown_detailed' for full details with context"New value: +"Response format: 'json' for structured, round-trippable data (default), 'markdown' for human-readable output, 'markdown_concise' for a brief summary (1-2 paragraphs), or 'markdown_detailed' for full details with context"
  2. Addedv1.1.0

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already indicate destructive and open-world behavior, but the description goes much further: it explains row shifting, the protected header, table relocation causing tableId changes, the response returning the current tableId and previousTableId, and the recompile side effect. These are critical behavioral details beyond what the annotations or schema provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively long but dense with necessary caveats: id volatility, recompile behavior, and response semantics. It is front-loaded with the core delete behavior and each sentence adds operational value, though a few details repeat what is already in the schema.

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 that there is no output schema, the description appropriately explains the key response detail, the current tableId and previousTableId, and it warns about the table's id changing. It covers destructive behavior, positional constraints, and the recompile side effect well, though it does not describe error cases or the full response shape.

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 100%, so the baseline is 3 even without extra parameter detail. The description reinforces the default count and the meaning of position, but most parameter semantics are already fully documented in the input schema; the main added value is clarifying that the returned tableId may change after relocation.

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 operation: deleting one or more rows from a table's raw source, starting at a given position, with rows below shifting up. It also clarifies scope limits such as the header row being undeletable and positions being 0-based, making it easy to distinguish from sibling tools like openl_delete_table_columns or openl_update_table_row.

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 gives useful context by noting that this operates on the RAW source and works for any table type, which implies broad applicability. However, it does not explicitly mention sibling alternatives or state when not to use this tool, such as when deleting columns or the whole table instead.

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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