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openl-tablets

OpenL MCP Server

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Append Rows/Fields to Table

openl_append_table
Idempotent

Append new data to any OpenL table type: fields for Datatype, rules for Rules, steps for Spreadsheet, values for Vocabulary, or rows for RawSource. Returns the table's current ID.

Instructions

Add new rows/fields to an existing table (additions only). Payload by type: Datatype→fields, SimpleRules/SmartRules→rules, SimpleSpreadsheet→steps, Spreadsheet→rows+cells, Vocabulary→values, RawSource→rows. For RawSource, each row must cover ALL columns of the table (one cell object per column; rows with a wrong cell count are rejected before anything is written). For modifying, deleting, or reordering use update_table instead. IMPORTANT: 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 all subsequent calls. Note: the studio does not auto-compile after an edit (it only resets the previous compile status); this tool reads the table back after appending to trigger the recompile, so a subsequent openl_project_status reflects the change.

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.
appendDataYesData structure to append to the table. Structure depends on tableType: Datatype uses 'fields'; SimpleRules/SmartRules use 'rules'; SimpleLookup/SmartLookup use 'rows' (array of maps); Data/Test use 'rows' (array of { values }); SimpleSpreadsheet uses 'steps'; Spreadsheet uses 'rows' (row headers) + 'cells' (2D cell array); Vocabulary uses 'values'; RawSource uses 'rows' (array of cell-arrays).
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?

Discloses key behavioral traits beyond annotations: table ID can change if relocated, recompile is triggered, RawSource row width requirements, and that rows with wrong cell count are rejected before writing. No contradiction with annotations.

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?

Dense and informative, front-loaded with core purpose. Slightly long but well-structured and each sentence adds necessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Thoroughly covers all table types' payload structures, important side effects (id change, recompile), and response behavior. No output schema, but description adequately explains what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage, baseline is 3. The description adds value by summarizing the payload structure per tableType and clarifying RawSource format, but some details are already in 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?

The description clearly states 'Add new rows/fields to an existing table (additions only)' with a specific verb and resource. It distinguishes from sibling tool 'update_table' for modifications, deletions, or reordering.

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 says 'For modifying, deleting, or reordering use update_table instead.' Also provides important context about when to use (additions) and when not to (other operations).

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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