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dl_object_create

Create typed DataLens drafts or local JSON artifact references in dependency order, then save and read them back for validation.

Instructions

Create typed DataLens drafts or local JSON artifact references ({artifact_path: absolute path}) in dependency order, save, and read back. A typed Dataset uses top-level object_type/name/client_ref and nested dataset.connection_id/source/fields. References may override client_ref/depends_on only.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "drafts": "<drafts>",
      "destination": "<destination>"
    },
    "name": "dl_object_create"
  }
}

Input Schema

Name	Required	Default
`drafts`	Yes
`destination`	Yes
`operation_id`	No
`delivery_mode`	No	save

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedv1.2.27Oct 7, 2026

addedInput schema / properties / drafts / items / properties / dashboard

Added value: +{
+  "description": "Typed tabs/items including selector_group; chart placement requires concrete hint text. Supports project_root and presentation.",
+  "type": "object"
+}

addedInput schema / properties / drafts / items / properties / dataset_fields

Added value: +{
+  "description": "Dataset field readback for complete offline Wizard payload validation.",
+  "items": {
+    "additionalProperties": true,
+    "properties": {
+      "aggregation": {
+        "minLength": 1,
+        "type": "string"
+      },
+      "data_type": {
+        "minLength": 1,
+        "type": "string"
+      },
+      "formula": {
+        "type": "string"
+      },
+      "guid": {
+        "minLength": 1,
+        "type": "string"
+      },
+      "name": {
+        "type": "string"
+      },
+      "title": {
+        "type": "string"
+      }
+    },
+    "required": [
+      "guid"
+    ],
+    "type": "object"
+  },
+  "type": "array"
+}

addedInput schema / properties / drafts / items / properties / validation_scope

Added value: +{
+  "description": "Static single-draft scope; batch draft validation uses complete_draft. SDK create supplies omitted provider-required tabs.",
+  "enum": [
+    "complete_draft",
+    "supplied_tabs"
+  ]
+}

addedInput schema / properties / drafts / items / properties / wizard

Added value: +{
+  "description": "Typed Wizard settings; family, project_root and presentation resolve the shared visual profile.",
+  "type": "object"
+}

Addedv1.2.0Sep 12, 2026

TDQS

B3.2/5.0

Behavior3/5

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

Annotations already declare readOnly=false, idempotent=false, destructive=false, and openWorld=true, so the safety profile is covered. The description adds useful beyond-annotation context: creation happens in dependency order, results are saved and read back, and references may only override client_ref/depends_on. It does not disclose failure behavior, auth/permission needs, or partial-create semantics.

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?

Two sentences, front-loaded with the verb and the primary object, with no filler. It is tightly packed to the point of being dense, but every clause carries payload rather than redundancy.

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?

For a complex nested-object creation tool with no output schema and low schema coverage, the description is only partially complete. It covers the draft payload shape but omits destination resolution, operation_id usage, delivery_mode semantics, and error/readback behavior an agent needs to invoke it confidently.

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?

Top-level schema description coverage is 0%, so the description must compensate. It explains the draft shape (top-level object_type/name/client_ref with nested dataset.connection_id/source/fields) and that artifact_path is an absolute path, adding real meaning beyond the schema. However, destination's three modes (workbook_id/collection_id/path), operation_id, and delivery_mode are left unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Create) and resource (typed DataLens drafts or local JSON artifact references) with concrete scope, including the dependency-ordered save/readback flow. It is distinguishable from siblings like dl_object_update or dl_object_publish, though the dense jargon slightly obscures the plain-purpose statement.

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

Usage Guidelines2/5

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

No when-to-use guidance, no prerequisites, and no alternatives named despite a rich sibling set (dl_object_update, dl_object_publish, dl_compile_recipe). The mention of 'dependency order' implies ordering behavior but does not tell the agent when to prefer this tool over others.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.