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Build something that is not there yet

Reconcile payroll to the general ledger every pay period

  • When payroll expense in the GL doesn't match the payroll register and nobody can say why by how much.
  • When an off-cycle payroll run threw the monthly tie-out off and it took days to trace.

Build a tie-out mart between the payroll register and GL payroll postings at pay period and cost center grain, with breaks classified by mechanism and tolerance tests. Covers the reconciliation, not the payroll calculation itself.

Area
Transformation
Runs on
  • Microsoft Fabric Lakehouse
  • Microsoft Fabric Warehouse
  • MotherDuck
  • DuckDB
Built with
  • dbt
  • dlt
Domain
People
Industry
Manufacturing, Retail, Healthcare
Readiness
SupportedEverything this Recipe composes runs today, without a case that proves this exact shape.
Before you start
carries personal data; reconcile at aggregate grain by default

Sample This Recipe has not been materialized in the Cookbook repository yet. Its trigger, description, prompt, agent guidance and acceptance conditions, and the explanation below, are prototype drafts. Its name, job, area and readiness come from the reconciled Cookbook seed snapshot. Readiness is a separate question from this one: it says whether the capability exists, not whether the writing has been reviewed.

Use this Recipe

Use the VibeData Recipe `people-payroll-gl-tieout` at https://getvibedata.ai/cookbook/people-payroll-gl-tieout Read the Recipe and execute it in the context of the current Intent.

Recipe id people-payroll-gl-tieout · Not yet materialized in the Cookbook repository, so the pointer addresses this page.

Verified by

What has to be observably true before this Recipe is finished.

  • the payroll register total ties to GL payroll postings within tolerance for a normal pay period
  • an accrual spanning month-end lands in the period the agreed accrual rule assigns it to
  • an off-cycle run is identified and classified rather than folded into the regular period's break
  • register-level detail is reconciled at aggregate grain unless a specific break requires drill-down
Recipe promptThe task specification the agent reads. Reference only — it is not what you copy.
Deliver: Reconcile payroll to the general ledger every pay period.

Build a tie-out mart between the payroll register and GL payroll postings at pay period and cost center grain, with breaks classified by mechanism and tolerance tests. Covers the reconciliation, not the payroll calculation itself.

Execute inside the current Intent. Its Domain, repository, platform, environment and attached sources are the context for this work — read them rather than asking for them.

The work is done when:
- the payroll register total ties to GL payroll postings within tolerance for a normal pay period
- an accrual spanning month-end lands in the period the agreed accrual rule assigns it to
- an off-cycle run is identified and classified rather than folded into the regular period's break
- register-level detail is reconciled at aggregate grain unless a specific break requires drill-down

Report the evidence for each condition above with the result. A condition you cannot meet is something to say, not something to work around.
Agent guidanceHow the agent approaches the work, and what it will not do.

Profile the inputs the grain, joins and measures actually depend on before proposing a model. Put the design up for review — grain first — then build in an isolated copy with tests and documentation landing beside the model rather than after it.

Composes

  • dbt model authoring and layering
  • dbt in the project
  • dlt in the project
  • isolated-copy execution and gate verification

Asks first

Semantic decisions the Intent cannot supply. Never context Studio already holds.

  • which Fabric target this work lands on, when the Domain carries both a Lakehouse and a Warehouse
  • the grain the requester expects, where the request leaves it open to more than one reading

Guardrails

  • Build in an isolated copy. Production is read, never written.

What you need

  • Microsoft Fabric Lakehouse, Microsoft Fabric Warehouse, MotherDuck, or DuckDB.
  • A dbt project you can build, and read access to the models it starts from.
  • dbt and dlt in the project, or the intent to add it.
  • Carries personal data; reconcile at aggregate grain by default.

How it goes

  1. State the outcome in one sentence, in the language the request arrived in.
  2. Let it profile the inputs the grain, the joins and the measures actually depend on.
  3. Review the design. Disagreeing about grain here costs a sentence; after the model exists it costs a rewrite.
  4. Let it build in an isolated copy, with the tests and the documentation landing beside the model rather than after it.
  5. Read the acceptance conditions against the run.

What you end up with

The deliverable, in your own repository, as transformation work a reviewer who knows the project reads as native to it. Alongside it, the evidence for every one of the acceptance conditions above — which is the part that is still there in three weeks when somebody asks.

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