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josemachado-vp

SF Assistant MCP Server

execute_upsert

Upsert records to a SuccessFactors entity in batches. Use dry_run mode to validate before writing data.

Instructions

Execute an upsert operation against an SF entity.

IMPORTANT: Defaults to dry_run=True. In dry_run mode, validates all records against metadata without making any changes. Set dry_run=False to actually write data.

Records are processed in batches. Each record is sent as an individual OData POST (upsert) to the entity endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNoIf True (default), validates without writing. Set to False to actually execute.
recordsYesList of record dictionaries to upsert
batch_sizeNoRecords per batch (1-50)
data_centerNo
entity_nameYesTarget SF entity
auth_user_idNo
auth_passwordNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Discloses key behaviors: dry_run default and its effect, batch processing, and individual OData POST per record. With no annotations, the description carries full burden and meets it well, though could add error handling details.

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 paragraphs with no filler. Each sentence adds value: purpose, important default, and processing mode. Highly concise and front-loaded.

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?

Covers operation, dry_run mode, and batching. With output schema present, return values are expected to be documented. Missing auth context and error handling but sufficient for understanding the tool's core behavior.

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 57%, and description adds value by explaining dry_run default and batch processing. However, it does not compensate for underspecified parameters like data_center and auth fields. Parameter semantics are adequate but not enhanced significantly.

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?

Description clearly states 'Execute an upsert operation against an SF entity', specifying the verb 'execute' and the resource. It distinguishes from sibling tools like query_odata (read-only) by being a write operation.

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 explicit guidance on when to use this tool versus alternatives. The description does not mention comparable tools or exclusion criteria, leaving the agent without context for tool selection.

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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