Software License Evidence Packet
Reconcile software entitlements, assignments, usage, invoices, renewals, credits, and deprovisioning evidence without turning assumptions into compliance claims.
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You say
We are preparing an annual renewal for a seat-based analytics platform. I uploaded the signed order form, renewal quote, three invoices, current admin-user export, SSO roster, HR status export, deprovisioning tracker, and procurement workbook.
The order form shows 600 named-user seats. The admin export has 643 assignments. SSO shows 571 people active in the last 90 days. HR marks 31 assigned users as terminated. There are also 20 service/shared accounts and duplicate identities after an acquisition.
Build a traceable software-license evidence packet. Reconcile the populations, show transparent true-up scenarios, identify what is supported versus unresolved, and do not decide contract interpretation, compliance, or what we owe the vendor.
Your agent does
Software-License Evidence Packet:
- Purchased baseline: 600 named-user seats
- Current assignments: 643
- HR-confirmed terminated but assigned: 31
- Service/shared accounts: 20 — treatment unresolved
- Raw delta: +43
- Confirmed-removal scenario: 612 candidate assignments / +12 versus baseline
- Duplicate candidates: held for stable-ID review
- Compliance/vendor liability: not decided
Deliverables: source register, entitlement register, identity crosswalk, exception register, invoice/renewal reconciliation, scenario matrix, evidence gaps, reviewer questions, and handoff summary.
What you get
About this skill
Software licensing reviews often break because agreements, order forms, admin exports, SSO and HR identities, device inventories, usage reports, invoices, renewal quotes, credits, and deprovisioning records describe different populations.
Software License Evidence Packet gives an AI agent a disciplined workflow for turning those supplied records into one traceable review package.
It builds a source register and entitlement ledger, keeps named-user, device, installation, consumption, and concurrent metrics separate, crosswalks identities, flags terminated or stale assignments, duplicate candidates, service and automation accounts, invoice and renewal mismatches, and produces transparent true-up or renewal scenarios with assumptions clearly labeled.
It does not interpret contracts, certify compliance, validate vendor claims, decide whether a specific account consumes a license, approve true-ups, authorize payments, or access live vendor systems.
Ideal for software asset management, IT asset management, procurement, finance, IT operations, internal audit-support, and renewal-review workflows.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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