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Delete DataLens workbook

datalens_workbooks_delete
Destructive

Delete a DataLens workbook and all its contents: connections, datasets, charts, dashboards. Use this to remove a workbook entirely; re-read before retrying after a server error.

Instructions

Delete a workbook with everything it holds: connections, datasets, charts, dashboards.

Deleting a workbook that is already deleted answers 500, not 404: after a server error, read the workbook before deleting it again.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workbook_idYesWorkbook id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.122.1

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and idempotentHint=false, so the safety profile is covered. The description goes beyond that by naming exactly what is destroyed (connections, datasets, charts, dashboards) and by documenting a non-obvious error behavior that confirms the non-idempotency hint. Still silent on permissions and on what a successful response returns.

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?

Two sentences, both earning their place: the first states scope of destruction, the second the failure/retry quirk. Front-loaded with the essential destructive scope.

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?

For a one-parameter destructive tool with no output schema and strong annotations, the description covers the destruction footprint and a real failure-mode gotcha. Missing auth/permission requirements, which would be the remaining gap.

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?

Only one parameter, and the schema documents it at 100% coverage ('Workbook id.'). The description adds no format, source, or lookup guidance for the id, so it does not exceed the schema baseline.

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?

Specific verb+resource (delete a workbook) plus an explicit statement of cascade scope: connections, datasets, charts, dashboards. That scope detail separates it from datalens_workbooks_delete_bulk and datalens_charts_editor_delete without any schema lookup.

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?

Implicit usage is clear (deleting a single workbook), and the description gives a useful retry rule for the 500-not-404 case. But it never states when to prefer this over datalens_workbooks_delete_bulk, nor any permission or prerequisite conditions.

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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