Inventory Adjustment Evidence Packet
Organize counts, balances, movements, lots, serials, transfers, write-offs, approvals, valuation, journals, and investigations into a traceable evidence packet.
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You say
Organize these records for SKU-55: W1 (WMS) shows 100 units. C1 (Count) shows 92. T1 (Transfer) shows 10 units arrived 10 mins before W1. M1 (Manager) proposes an 8 unit write-off. standard cost $50.
Your agent does
Decision: PARTIAL INVENTORY-ADJUSTMENT EVIDENCE PACKET AVAILABLE. Provisional 8-unit variance identified. Gaps: Transfer T1 arrival vs W1 snapshot inclusion is unverified. Requests: Reconstruct T1 posting time and confirm if C1 included the 10 transferred units. Draft adjustment: $400.00.
What you get
About this skill
The problem
Inventory discrepancies between system balances and physical counts often lead to premature write-offs or unverified shrinkage claims. Operations and finance teams struggle to reconstruct movement cutoffs, status changes, and unit conversions across fragmented records without losing traceability.
What it does
- Organizes physical counts, recounts, and system snapshots into a unified, traceable evidence packet.
- Reconstructs inventory chronologies by mapping receipts, picks, transfers, and returns against count freeze times.
- Distinguishes between physical on-hand, reserved, allocated, quarantined, and in-transit stock populations.
- Identifies gaps in serial number history, lot tracking, and unit-of-measure conversions.
- Surfaces specific conflicts such as duplicate transfer postings, omitted locations, or unsupported valuation claims.
Why this beats prompting it yourself
This skill enforces a strict neutral stance, preventing the AI from making unauthorized accounting decisions or guessing at root causes. It implements a rigorous 26-step workflow that ensures system postings and physical movements are never conflated, providing a source-indexed ledger ready for professional audit review.
Use cases
- Reconciling warehouse cycle counts where first and second counts show unexplained variances.
- Auditing omnichannel retail locations where ecommerce reservations and store returns overlap.
- Reconstructing movement cutoffs for high-value serialized assets during facility transfers.
- Preparing evidence packets for finance teams to review before approving inventory adjustments or journal entries.
Known limitations
Requires user-supplied files or data via the Read tool. It cannot access live ERP, WMS, or POS systems directly, nor can it certify financial accuracy or prove employee misconduct.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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