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 that document production without removing the human judgment that HR work requires. With Scaffold MCP connected to Claude, HR professionals can generate offer letters, draft PIPs, and redline policies 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: Template + Fill in One Conversation
An offer letter has a fixed structure and a handful of variable fields: candidate name, job title, department, compensation, start date, manager, and any conditional terms like signing bonus or relocation allowance. That structure makes it an ideal template automation candidate.
Building the template. Start with an offer letter you've already sent — one that legal or HR leadership has approved. Open it in Word and replace every variable element with a labeled placeholder: ,, ,, ``. Keep the approved boilerplate, the at-will language, and any jurisdictional disclosures exactly as they are. Upload the file to Scaffold as a template.
Generating the document. In Claude with the Scaffold MCP connector active:
"Generate an 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 fills the template, maps each piece of information to the right placeholder, and produces a download link for a complete .docx file. The formatting matches your original exactly. You review, add any hire-specific notes in the body if needed, and send.
What doesn't change. The legal language, the at-will clause, the arbitration provision, the benefits disclosure — none of that is touched. Claude fills only the fields you designated. This is an important distinction from asking Claude 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 template 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 create a template that locks in 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 describe the situation to Claude and it drafts the specific language to fill each section.
"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. Use our standard PIP template."
Claude produces a filled document with language specific to the situation you described. You review it, make any adjustments — perhaps softening language, adding context, adjusting a specific metric — and save the final version.
The output is a Word .docx with the specific language drafted 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 comment explaining why that edit was made. You review each proposed change individually, accepting or rejecting it in Word as you normally would. 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, your entire HR team shares a single Scaffold template library. Upload your approved templates once — offer letters for each employment classification, your standard PIP structure, your handbook policy sections — and every team member can generate from them without needing their own template copies. Template updates propagate to everyone immediately.
Access controls are coming in a future release. For now, templates are visible to all team members. The practical workaround is naming templates clearly enough that people use the right one — "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 — verbally to Claude. This is intentionally simple: no API integrations, no CSV imports, no structured data requirements. You describe the hire; Claude fills the document.
If you're an HR team spending more than a few hours a week on document production, Scaffold MCP with Claude is worth a look. The free 7-day trial at app.scaffoldyourdocs.com/sign-up gives you full access to templates and redlining. Set up takes about ten minutes.