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josemachado-vp

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validate_rule_fields

Validate business rule fields by confirming entities, fields, and picklist values exist in SAP SuccessFactors metadata, and check field types and editability.

Instructions

Validate that fields, entities, and picklist values referenced in a proposed business rule actually exist in the SAP SuccessFactors instance.

For each field:

  1. Verifies the entity exists in $metadata

  2. Verifies the field exists on that entity

  3. Checks the field type (string, date, picklist, number)

  4. If picklist values are provided, verifies they exist

  5. Checks if the field is editable (creatable or updatable)

Example fields_to_validate: [ {"field": "payGroup", "entity": "EmpJob", "values": ["PG_PE_FT", "PG_PE_PT"]}, {"field": "employeeClass", "entity": "EmpJob", "values": ["FT", "PT"]}, {"field": "countryOfCompany", "entity": "EmpJob"} ]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
base_objectNo
data_centerNo
auth_user_idNo
auth_passwordNo
fields_to_validateYesList of fields to validate. Each dict: {'field': str, 'entity': str, 'values': [optional list of picklist values]}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations provided, so description carries full burden. It lists five validation steps but does not disclose output format, error handling, or authentication needs, leaving behavioral gaps.

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?

Concise with a clear purpose statement, enumerated steps, and an illustrative example; no unnecessary information.

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

Completeness3/5

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

Output schema exists but is not described. Missing details on return values, error messages, and how optional parameters affect behavior, leaving some incompleteness for a 5-parameter tool.

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 20%. Description adds value for fields_to_validate with structure and example, but ignores four optional parameters (base_object, data_center, auth_user_id, auth_password), so only partial compensation.

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 fields, entities, and picklist values for business rules, with specific steps and an example, distinguishing it from sibling tools like validate_country_compliance.

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

Usage Guidelines3/5

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

Context is implied by 'proposed business rule' but no explicit guidance on when to use versus alternative validation tools, nor any when-not-to-use conditions.

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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