datalens_sqlqueries_deleteDelete a specific saved SQL query by its ID. Use this tool to remove queries from DataLens and keep your workspace organized.
Delete a saved SQL query.
Experimental in the DataLens API and written from its document: not measured.
| Name | Required | Description | Default |
|---|---|---|---|
| sql_query_id | Yes | SQL query id. |
Changes observed during successful MCP inspections.
v0.122.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, idempotentHint=false, and openWorldHint=true, so the safety profile is fully covered by structured fields. The description's only added context is the experimental/unmeasured caveat, which is genuine behavioral information but does not disclose what is destroyed or any auth requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very short and front-loaded: the action is stated first, followed by a brief caveat. Every sentence is relevant, though the experimental note is phrased awkwardly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter delete with rich annotations and no output schema, the description is minimally sufficient. It lacks any usage context or confirmatory detail (e.g., irreversibility, error on missing id), leaving gaps an agent might care about.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There is a single parameter with 100% schema description coverage ('SQL query id.'), so the schema already carries the semantics. The description adds nothing about the id format or how to obtain it, which is acceptable but not enriching.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a clear verb ('Delete') and resource ('saved SQL query'), and 'saved' usefully distinguishes it from the sibling datalens_sqlqueries_run, which executes rather than removes a query. It stops short of explicitly routing against the other sqlqueries siblings, but the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as datalens_sqlqueries_get or update. The second sentence describes API maturity, not when or when-not to invoke the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.