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ADIKANT

datalens-dev-mcp

by ADIKANT

Validate Object

dl_validate_object

Validates an OpenAPI-backed object payload for DataLens objects (dashboards, charts, datasets, etc.) without mutation. Supports create, update, and validate operations.

Instructions

Validate an OpenAPI-backed object payload without mutation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payloadYesObject payload or RPC payload. Must not contain secrets.
operationNoObject operation to validate.update
object_typeYesGuarded lifecycle object type.
source_adapterNoNamed lifecycle source adapter.
execute_validationNoexecute_validation input.
approval_provenanceNoapproval_provenance input.
Behavior2/5

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

With no annotations, the description must convey behavioral traits. It only states 'without mutation,' missing details on required permissions, side effects, rate limits, or what happens on success/failure. The schema hints at approval provenance but the description ignores this.

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?

Extremely concise, front-loaded single sentence with no wasted words. Clearly states core purpose and a key constraint.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 6 parameters, no output schema, and no annotations, the description is insufficient. It fails to explain what the tool returns (e.g., validation errors), how to interpret results, or any side effects beyond mutation.

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 coverage is 100%, so baseline is 3. The description adds no parameter-specific context beyond what the schema already provides. It does not explain the role of 'operation' or 'execute_validation'.

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 clearly states the tool validates an object payload and specifies it is non-mutating. It identifies the resource and action but does not explicitly differentiate from sibling validation tools like dl_validate_project or dl_validate_source_availability_consumers.

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 guidance on when to use this tool versus alternatives. The note 'without mutation' implies it is safe for read-like operations, but there is no mention of prerequisites, limitations, or explicit context for use.

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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