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wudaoyou

successfactors-mcp

by wudaoyou

compare_metadata

Compare OData metadata across two SAP SuccessFactors instances to find configuration drift, missing fields, and changed attributes per entity or service.

Instructions

Compare the OData configuration of two instances and return the drift.

entity="EmpJob" compares one entity set; entity="" compares the whole service (v4: a service path, as in odata_metadata). The comparison runs here, not in the conversation: one instance's EmpJob metadata alone is ~40 KB, so diffing two of them in context is both expensive and easy to get wrong.

Returns in_sync plus, per entity, the fields missing on either side and the fields whose attributes differ, each as [value_in_a, value_in_b]. The sap: attributes are the configuration itself — required, visible, upsertable, picklist, MaxLength — so a changed picklist or a field that never left the dev instance shows up here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entityNo
company_aYes
company_bYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does fairly well: it discloses that the diff executes server-side, justifies it with the ~40 KB payload size, and explains the shape of the result ([value_in_a, value_in_b] pairs, missing vs. differing fields). It omits permissions/auth requirements and any rate or size limits on the comparison itself.

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

Conciseness4/5

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

Front-loads the purpose, then parameter nuances, then the justification and return shape. The 40 KB rationale sentence is longer than strictly needed but earns its place by preempting the obvious 'why not just fetch both?' objection.

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?

An output schema exists, yet the description still sketches the return contract and the meaning of the `sap:` attributes, which is useful domain framing rather than duplication. For a three-parameter diff tool with no annotations, this is close to complete; only the company identifier semantics are thin.

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 description coverage is 0%, so the description must compensate and it only partially does. `entity` is well specified ('EmpJob' vs. empty string / v4 service path), but `company_a` and `company_b` are left to inference from the phrase 'two instances' with no statement of expected format or how instance identifiers are obtained.

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?

States a specific verb and resource — 'Compare the OData configuration of two instances and return the drift' — and immediately names the output concept (drift, in_sync). It also differentiates from siblings by noting the comparison runs here rather than in the conversation and by referencing odata_metadata for the service-path semantics.

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?

Explains the scoping choices for the `entity` parameter (single entity set vs. whole service) and gives a clear rationale for using the tool instead of diffing metadata manually in context. It does not explicitly route against the other siblings (odata_query, list_tenants), so it stops short of a full when/when-not map.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.