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🪑 SaaS License Utilization Reconciler
Reconcile SaaS seats, activity, invoices, and HR status into reviewable reclaim candidates without revoking access.
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You say
users[] uses user_id and employment_status; licenses[] uses license_id, user_id, application, status, days_since_activity, and optional exception evidence; invoices[] uses invoice_id, application, and seat_count.
Your agent does
A deterministic READY, REVIEW, or BLOCK result with stable finding codes, a complete review manifest, a human-readable report, and a SHA-256 receipt.
What you get
About this skill
SaaS License Utilization Reconciler turns owner-supplied normalized evidence into a deterministic local review gate. Assigned seats, recent activity, invoices, contracts, and HR rosters are commonly compared by hand immediately before renewal. The bundled Python helper writes stable findings, a complete review manifest, JSON and Markdown reports, and a SHA-256 receipt. Produces stable terminated-user, unused-seat, duplicate-assignment, and invoice-count findings while keeping every access change outside the package. It uses only the Python standard library, makes no network request, changes no account or system, and never treats READY as source proof, certification, a legal or security verdict, a reimbursement promise, or authorization to act.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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Creator
JustHandled Labs builds focused agent skills for the work nobody wants to do by hand. Each one is a single repeatable job done well: catching the security and data mistakes that quietly ship, keeping docs and tests honest, gating the commands an agent is about to run, sharpening writing, and handling the founder chores around launches, outreach, and brand setup. Not generic AI productivity. Specific workflows that are easy to run, review, and repeat. Maintained by H.J. Westerfield, with a background in communications, editing, project coordination, customer support, and practical AI systems. Tools for people who want useful automation without theatrical complexity.
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