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openl-tablets

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openl Update Table

openl_update_table
Idempotent

Replace the complete table structure to modify, delete, or reorder rows. Must pass the full modified object retrieved via get_table().

Instructions

Replace the ENTIRE table structure with a modified version. Use for MODIFYING existing rows, DELETING rows, REORDERING rows, or STRUCTURAL changes. CRITICAL: Must send the FULL table structure (not just modified fields). DO NOT use for simple additions - use append_table instead. Required workflow: 1) Call get_table() to retrieve complete structure, 2) Modify the returned object, 3) Pass the ENTIRE modified object to update_table().

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID returned by backend. Use the exact 'projectId' value from openl_list_projects() response without modification or reformatting.
tableIdYesTable identifier - unique ID assigned by OpenL Studio when table is created (e.g., 'calculatePremium_1234')
viewYesFULL table structure from get_table() with your modifications applied. MUST include: id, tableType, kind, name, plus type-specific data (rules for SimpleRules, rows for Spreadsheet, fields for Datatype). Do NOT send only the changed fields - send the complete structure. Workflow: 1) currentTable = get_table(), 2) currentTable.rules[0]['Column'] = newValue, 3) update_table(view=currentTable)
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 give idempotentHint and openWorldHint, but the description adds critical behavioral context: the tool replaces the entire structure, requires sending the full structure, and warns against partial updates. 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?

The description is front-loaded with the main purpose and includes necessary warnings and workflow. While slightly lengthy, every sentence contributes meaning. Minor room for tightening, but still highly effective.

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?

Given the tool's complexity (3 required params, nested objects, no output schema), the description is thorough. It covers workflow, required structure, alternatives, and response format options, making it complete for agent invocation.

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

Parameters5/5

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

Schema coverage is 100%, but the description significantly enhances meaning for 'view' with workflow steps and warnings about sending the full structure. It also clarifies projectId and tableId usage. This adds substantial value 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?

The description clearly states the tool replaces the entire table structure, specifying the verb 'replace' and resource 'table structure'. It distinguishes from the sibling openl_append_table by explicitly stating not to use for simple additions, ensuring the agent understands the scope.

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?

Provides explicit when-to-use (modifying, deleting, reordering rows, structural changes) and when-not-to-use (simple additions, refer to append_table). Includes a required workflow (call get_table, modify, pass full object), offering clear 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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