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Find DataLens entries

datalens_entries_list
Read-onlyIdempotent

List DataLens entries across the organization: dashboards, charts, datasets and connections. Filter by scope, ids or type, and sort by name or creation date.

Instructions

Entries across the whole organization: dashboards, charts, datasets, connections.

The API requires one of scope, scopes and ids. An entry the caller may not read comes with isLocked set and little else. Auto-paginated; capped at the configured item cap unless limit is given.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsNoKeep the entries with these ids.
typeNoKeep these types of entries.
limitNoMax entries to return; omitted means the configured cap (YCLI__HTTP__MAX_ITEMS).
scopeNoKeep one kind of entry.
scopesNoKeep several kinds of entries.
filtersNoKeep the entries whose name has a text.
order_byNoWhat to sort by and in which direction.
created_byNoKeep what these users created.
include_dataNoAlso give the content of each entry (large).
include_linksNoAlso say what each entry is linked to.
exclude_lockedNoLeave out the entries the caller may not read.
ignore_shared_entriesNoLeave out the shared entries.
ignore_workbook_entriesNoLeave out the entries that lie in workbooks.
include_permissions_infoNoAlso say what the caller may do with it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.122.1

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint), and the description still adds genuine behavior: unreadable entries return with isLocked and almost no other fields, results are auto-paginated, and output is capped at the configured item cap unless limit overrides it. Those are non-obvious traits an agent could not derive from structured fields.

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 sentences, front-loaded with the resource and scope, then the invocation constraint, then return/pagination behavior. No filler, and the most important constraint appears before the edge-case details.

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 14-parameter read tool with no output schema, the description covers the essential constraints and the locked-entry return quirk, while the schema documents every parameter including include_data's 'large' warning. It stops short of naming the workbook-scoped or collections-content alternatives, which an agent scanning ~300 siblings would likely want.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema by stating the one-of scope/scopes/ids requirement that the schema's empty required list contradicts, and by explaining that limit overrides the global cap rather than merely bounding the page.

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?

The description names the resource (entries), enumerates concrete types (dashboards, charts, datasets, connections) and fixes the scope as 'across the whole organization'. That scope statement implicitly separates it from the sibling datalens_workbooks_entries_list, but the alternative is never named, so the differentiation is left for the agent to infer.

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?

It supplies a real prerequisite that the schema does not encode: the API requires one of scope, scopes or ids even though the input schema marks nothing as required. There is no explicit when-not or named alternative (e.g. the workbook-scoped sibling), which keeps it below a 5.

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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