HR Documents with AI: Offer Letters, PIPs, and Policies as Tracked Changes
How HR teams can use Scaffold MCP with Claude to revise offer letters, draft PIPs, and redline policy updates — with full tracked-change auditability.
HR teams generate a large volume of documents that follow predictable structures but require specific, accurate variable content — compensation figures, role titles, performance metrics, regulatory references. AI document automation reduces the time spent on those documents without removing the human judgment that HR work requires. With Scaffold MCP connected to Claude or ChatGPT, HR professionals can have their AI propose edits to offer letters, PIPs, and policies as Word tracked changes, and approve each one, without leaving their AI workspace.
The distinguishing feature for HR use specifically: every AI-proposed change is a tracked revision, not a silent edit. That matters for compliance.
Offer Letters: Tracked Edits in One Conversation
An offer letter has a fixed structure and a handful of details that change: candidate name, job title, department, compensation, start date, manager, and any conditional terms like signing bonus or relocation allowance. That structure makes it a good fit for reviewable, tracked edits.
Starting from an approved letter. Start with an offer letter you've already sent — one that legal or HR leadership has approved. Upload a copy of it to Scaffold as it is. There is nothing to mark up or convert first; the approved boilerplate, the at-will language, and any jurisdictional disclosures stay exactly as they are.
Proposing the edits. In Claude with the Scaffold MCP connector active:
"Update this offer letter for Marcus Reyes. He's joining as a Senior Data Analyst in the Finance department, reporting to Dana Kim. Salary is $92,000 annually. Start date is April 7."
Claude proposes each change — the name, title, department, manager, salary, start date — as a tracked change with its reason. You review them one at a time on the Track, approve or reject each, make any small fixes directly in the review pane, and download or email the .docx. The formatting stays your original's.
What doesn't change. The legal language, the at-will clause, the arbitration provision, the benefits disclosure — none of that changes unless a person approves a change to it. Any edit that touches those sections shows up as its own tracked change, so it can't slip through. This is an important distinction from asking an AI to "draft an offer letter from scratch," which produces a document that hasn't been reviewed by your legal team.
Performance Improvement Plans: Structured AI Drafting
A PIP is harder to reuse than an offer letter because the specifics matter more. A PIP for a missed sales quota looks different from one for a behavioral issue, which looks different from one for a remote-work attendance problem. But the structure is consistent: the performance concern, measurable goals, timeline, support offered, and consequence if goals aren't met.
Scaffold MCP handles this in two layers. First, you keep a standard PIP document with the structure and the required HR/legal boilerplate — the sections, the headings, the standard language about the process being a genuine improvement opportunity. Then, when you need a specific PIP, you upload a copy, describe the situation to Claude, and it proposes the specific language for each section as tracked changes.
"Draft a PIP for a sales account executive. The performance concern is that she's at 54% of quota for two consecutive quarters, against a team average of 88%. Goals should include reaching 75% quota in 30 days, 90% in 60 days, with weekly check-ins with her manager. The timeline is 90 days. Start from our standard PIP document."
Claude proposes language specific to the situation you described, each edit with its reason. You approve or reject each one, make any adjustments directly in the review pane — perhaps softening language, adding context, adjusting a specific metric — and the approved version is saved.
The output is a Word .docx with the specific language tracked in, not a chat message you have to copy-paste into a document. That matters when you're in a time-constrained situation and accuracy counts.
Policy Updates: Redlining When Regulations Change
HR policy documents need periodic updates when regulations change: minimum wage adjustments, FMLA rule changes, updated EEOC guidance, state-level paid leave additions. The challenge is that policy documents accumulate over years and the change isn't always obvious — a new federal rule might affect three different sections of a handbook without any single section being obviously wrong.
This is where the Scaffold MCP redlining workflow is most valuable for HR.
How policy redlining works with Scaffold MCP: Upload your current policy document to Scaffold, then describe the regulatory change to Claude. Ask Claude to identify every section that the change affects and propose amendments as tracked revisions. Claude will read the full document, locate the relevant passages, and produce a new version with each proposed change marked as a tracked revision — insertions underlined, deletions struck through, each change accompanied by a plain-English reason explaining why that edit was made. You review each proposed change individually on the Track, approving or rejecting it. Nothing is silently altered. Nothing is accepted until you explicitly accept it.
This is the auditability benefit that matters for HR compliance work specifically: every AI-proposed change is visible, reversible, and documented. If a regulator or auditor later asks why a policy was changed, you have a document trail showing what was proposed, what was accepted, and what was rejected. A silent AI edit that rewrites a policy paragraph without any tracked-change record is a compliance liability; a tracked-change revision that you reviewed and accepted is a standard document management record.
Why Tracked Changes Matter More for HR Than Other Teams
Most document teams value tracked changes as a convenience — it makes review easier. HR teams need them as a compliance mechanism.
Employment documents can be referenced years after they were created. An offer letter becomes evidence in a wage dispute. A PIP becomes evidence in a wrongful termination claim. A policy update becomes evidence in a class action. In each case, the question is often not just "what does the document say" but "who changed it, when, and why."
Tracked changes with AI-authored revisions give you a clear record: Claude proposed this change on this date, and the HR reviewer accepted or rejected it. That record has procedural value entirely separate from the quality of the edit itself.
Scaffold MCP preserves this record because it outputs standard Word tracked changes, not a rewritten clean document. The AI's contribution is visible and attributable. Your review decision is explicit.
Practical Setup for HR Teams
On a Team plan, at $5 per user per month, each member of your HR team gets their own access. Pro, at $5/month, covers a single HR professional. Either way, the approved documents you work from — offer letters for each employment classification, your standard PIP, your handbook policy sections — are uploaded as ordinary Word files.
Version history keeps every version of a document, with what went in and what was turned back. You can compare any two versions word by word, add a difference to the earlier version, or revert it in the later one. Clear names still help — "Offer Letter — CA Full-Time Exempt" and "Offer Letter — TX Full-Time Exempt" are unambiguous; "Offer Letter v3 Final FINAL" is not.
Integrating with your HRIS is not required. Scaffold MCP works from a conversation. You provide the specific data — compensation, dates, names — to Claude. This is intentionally simple: no API integrations, no CSV imports, no structured data requirements. You describe the hire; Claude proposes the edits; you approve them.
If you're an HR team spending more than a few hours a week on document revisions, Scaffold MCP with Claude or ChatGPT is worth a look. The Free plan at app.scaffoldyourdocs.com/sign-up gives you full access to redlining, the Track, and version compare for up to 10 documents, with no card required.