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validate_index

Validate your index YAML configuration against the deepset API to check for errors and receive the original YAML or an error message.

Instructions

Validates the provided index YAML configuration against the deepset API. :param yaml_configuration: The YAML configuration to validate. :returns: Validation result with original YAML or error message.

All parameters accept object references in the form @obj_id or @obj_id.path.to.value.

Examples::

# Direct call with values
validate_index(data={'key': 'value'}, threshold=10)

# Call with references
validate_index(data='@obj_123', threshold='@obj_456.config.threshold')

# Mixed call
validate_index(data='@obj_123.items', threshold=10)The output is automatically stored and can be referenced in other functions.

Returns a formatted preview with an object ID (e.g., @obj_123). Use the object store tools in combination with the object ID to view nested properties of the object. Use the returned object ID to pass this result to other functions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yaml_configurationYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It mentions validation, return of original YAML or error, automatic output storage, and object reference substitution, but does not disclose potential side effects (likely none).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is somewhat verbose with docstring-style tags and multiple examples. It could be more succinct while retaining key information.

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 single-parameter validation tool with no output schema, the description covers purpose, parameter format, object references, and output handling. It's complete but could mention that it's specifically for index configurations.

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 coverage is 0%, so description compensates. It explains the yaml_configuration parameter's purpose and demonstrates object reference usage, adding significant meaning beyond the schema.

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?

The description clearly states it validates YAML configuration against the deepset API. It distinguishes from siblings like create_index or validate_pipeline by focusing on validation of index configuration.

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?

Examples illustrate usage with direct values and object references, but it does not explicitly compare with validate_pipeline or other siblings. The reference mechanism is well explained.

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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