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List what DataLens entries use or are used by

datalens_entries_relations_list
Read-onlyIdempotent

List entry relations to see what an entry uses or what depends on it before changing or deleting it. Filter by kind and direction.

Instructions

What entries use (a chart's dataset, a dataset's connection) or what uses them.

Use it before changing or deleting an entry, to see what depends on it. Auto-paginated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax relations to return; omitted means the configured cap (YCLI__HTTP__MAX_ITEMS).
scopeNoKeep one kind of related entry.
entry_idsYesEntry ids.
link_directionNo`from`: what the entries use; `to`: what uses them.
include_permissions_infoNoAlso say what the caller may do with it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.122.1

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true and idempotentHint=true, so safety and idempotency are covered. The description adds 'Auto-paginated' and the dependency-check use case, but does not disclose return shape, permission implications, or other behavioral details beyond that.

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?

Three short, front-loaded sentences with no filler. Purpose, usage timing, and pagination behavior are each stated compactly and nothing is repeated unnecessarily.

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 5-parameter read-only list tool with full schema descriptions and annotations, the description covers purpose, when to call it, and pagination. It stops short of describing the returned relation structure, but the absence of an output schema makes that a minor gap rather than a critical omission.

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?

Schema description coverage is 100%, and the schema fully documents the limit, scope, entry_ids, link_direction and include_permissions_info parameters. The description's first sentence loosely echoes the link_direction concept but adds no syntax, defaults, or meaning beyond what the schema already provides.

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?

States a specific verb and resource: listing what DataLens entries use or are used by, with concrete examples (chart's dataset, dataset's connection). This dependency-relation purpose is clearly distinct from sibling list tools like datalens_entries_list or datalens_entries_revisions_list, even without naming them.

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

Usage Guidelines4/5

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

Explicitly says to use it before changing or deleting an entry to see what depends on it, which gives clear context for when to invoke it. It does not name alternative tools or when-not to use it, so it falls short of full 5-level routing 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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