msa-generation

name	msa-generation
description	Generate enterprise Master Services Agreements (MSAs) with accompanying proposals as Word documents (.docx). Use this skill whenever the user asks to create an MSA, master services agreement, service agreement, SaaS agreement, platform license agreement, or AI agent deployment contract. Also trigger when the user wants to formalize a client engagement that involves ongoing platform access, agent deployment, or technology licensing. This skill ingests meeting transcripts, presentations (.pptx), notes, and directory context to produce a complete MSA with scope of work, pricing, IP protections, performance milestones, and data portability provisions. Produces a polished, branded Ruh AI MSA ready for client signature. Triggers on: "MSA", "master services agreement", "service agreement", "create an MSA", "put together a contract", "draft the agreement", "formalize this deal", "SaaS agreement", "platform license", "agent deployment contract", "write up the MSA", "generate the contract".
allowed-tools	Bash, Read, Write, Glob, Grep, Agent

MSA Generation Skill

Overview

This skill creates enterprise-grade Master Services Agreements with integrated business proposals as branded .docx files. The MSA is designed for AI agent deployment engagements where Ruh AI builds, deploys, and operates autonomous agents on its proprietary platform for a client.

The generated MSA combines a business proposal (market opportunity, cost analysis, scope of work) with binding legal terms (IP, payment, termination, performance milestones, data portability) in a single document ready for signature.

When to Use

• User says "create an MSA" or "put together a contract" for a client
• User wants to formalize an AI agent deployment engagement
• User has meeting notes, transcripts, or presentations from a client discovery call and needs to turn them into a formal agreement
• User mentions master services agreement, service agreement, or platform license
• User references a client conversation and needs a comprehensive proposal + contract document

Step 1: Gather Context and Information

Before generating the MSA, collect information from all available sources. The skill should actively ingest:

Source Materials to Look For

1. Meeting transcripts — Extract client pain points, current state, desired outcomes, budget signals, key stakeholders, and any verbal commitments
2. Presentations (.pptx) — Extract scope details, phasing, pricing, and deliverables from existing slide decks. Use python3 -c "from pptx import Presentation; ..." to extract text
3. Notes and documents — Read any .md, .txt, .docx, or .pdf files the user points to
4. Directory context — Scan the working directory for relevant files (proposals, keyword research, competitor analysis, etc.)

Required Information

Collect from sources or ask the user for anything missing:

Field	Description	Example
Client Company	Legal entity name	Spyder Construction, LLC
Client State	State of organization	Colorado
Client City	Principal place of business	Littleton, Colorado
Client Contacts	Name(s) and title(s) of signers	Charlie Pappas, CEO; Damien Krebsbach, VP of Sales
Agent Type	What kind of agent is being deployed	AI Marketing Engine
Phase Label	Phase number and name	Phase 1: AI Marketing Engine
Build Fee	One-time build and deployment fee	$20,000
Monthly Fee	Ongoing platform license fee	$2,000/month
Payment Split	Build fee installment structure	50% on signing, 50% on go-live
PPC/Ad Spend	Recommended client ad budget (separate)	$3,000–$6,000/month
Token Cost Estimate	Estimated monthly LLM API costs	$50–$300/month
Timeline	Build and deployment timeline	8 weeks (2 discovery, 4 build, 2 testing)
Initial Term	Contract duration	12 months

Optional Information (use defaults if not provided)

Field	Default
Provider Entity	Ruh AI, Inc.
Provider State	Delaware corporation
Provider Location	Northern Idaho
Provider Contacts	Jesse Anglen, CEO; Luke Van Valin, VP of Sales
Renewal Term	12-month auto-renewal
Non-renewal Notice	30 days
Termination for Convenience Notice	60 days (after initial term)
Cure Period	30 days
Late Payment Interest	1.5% per month
Confidentiality Survival	3 years
Liability Cap	12 months fees
Governing Law	State of the client (show good faith)
Transition Assistance	30 days, up to 10 hours
Payment Terms	Net 15
Content Review Window	48 hours

Step 2: Build the Market Opportunity Section

If source materials contain keyword research, competitive analysis, or market data, build a compelling market opportunity section. This section should include:

1. Market Context — Why this client's niche is underserved digitally
2. Keyword Data — Actual search volumes, CPC estimates, competition levels (if available)
3. Competitive Landscape — What competitors are (or aren't) doing online
4. Cost Comparison — AI agent vs. traditional agency (annual cost table)

ROI Framing Rules

CRITICAL: Never use specific ROI multipliers or inflated revenue projections.

• Frame returns as "revenue opportunity" not "ROI"
• Use language like "closing even one additional deal per quarter would represent a significant return relative to the marketing investment"
• Never state specific multipliers (e.g., "12x–125x return")
• Never project specific revenue ranges from the marketing investment alone
• Let the client's own knowledge of their job values and close rates fill in the math
• The goal is credibility, not hype

Step 3: Generate the MSA Document

Use python-docx to generate the .docx file. The full reference structure is at references/msa-structure.md within this skill's directory.

Generation Process

1. Read the reference structure at references/msa-structure.md for section-by-section guidance
2. Create a Python script using python-docx to generate the document
3. Populate all sections with gathered information
4. Ensure python-docx is available: python3 -c "import docx" 2>/dev/null || python3 -m pip install python-docx
5. Run the script to generate the .docx
6. Present the generated file to the user

Document Structure

The MSA follows this exact structure:

1. Cover Page — Ruh AI branding, document title, phase label, client name, contacts, date, confidential
2. Executive Summary — Client's current state, the opportunity, what this proposal covers
3. Section 1: Market Opportunity — Digital landscape, keyword data, competitive analysis (if applicable)
4. Section 2: Cost Analysis — AI agent vs. traditional alternative, annual comparison table, projected results
5. Section 3: Scope of Work — Deliverables, timeline, what client provides
6. Section 4: Master Services Agreement — Services description, engagement structure (SaaS/license, not work-for-hire)
7. Section 5: Fees & Payment Terms — Fee schedule table, payment terms, late payment
8. Section 6: Intellectual Property & Ownership — Provider IP, license grant, client data, content ownership, no reverse engineering, data portability & transition assistance
9. Section 7: Term & Termination — Initial term, renewal, termination for convenience/cause, effect of termination, survival
10. Section 8: Confidentiality — Mutual obligations, exclusions, survival period
11. Section 9: Limitation of Liability & Performance — Liability cap, performance disclaimer, third-party platforms, performance milestones, service levels (SLA)
12. Section 10: General Provisions — Independent contractor, governing law, entire agreement, notices, severability, assignment (with client termination right on assignment)
13. Signature Page — Signature blocks for both parties

Key Provisions That Must Be Included

These provisions are non-negotiable and reflect our commitment to fair dealing:

Data Portability (Section 6.6)

Upon termination, deliver to client within 30 days:

• All keyword research, market segmentation, content strategy docs
• PPC campaign configurations, ad copy, audience targeting, performance data
• Content calendars and publishing schedules
• Analytics reports and dashboards
• 30-day transition assistance (up to 10 hours, no charge)
• Explicit carve-out: nothing grants rights to Provider's platform, agent code, AI models, or underlying technology

Performance Milestones (Section 9.4)

• Milestones conditioned on client fulfilling their obligations (ad spend, content publishing, platform access)
• If client fails their obligations, corresponding milestone is waived
• Month 6 exit ramp: client can terminate with 30 days' notice if milestone missed (and client met all obligations)
• Pro-rated build fee refund on early termination
• Mutual adjustment clause for market changes
• Measurement via shared analytics dashboards

Content Volume Framing

• Present as "capacity to produce up to X per day"
• State practical target as quality-controlled output (e.g., "15–25 high-quality articles per week")
• Include content review process: weekly digest, 48-hour flag window, 1-business-day removal

Service Levels

• 99% monthly uptime (excluding scheduled maintenance)
• 24-hour response for unscheduled disruptions
• Scheduled maintenance during off-peak hours (10 PM – 6 AM local)

Assignment

• Neither party assigns without consent
• Provider may assign in M&A
• Client gets 30-day termination right upon Provider assignment

Critical Rules

• This is a SaaS/license engagement, not work-for-hire. Always frame as client licensing access to the agent and platform, not purchasing ownership of software or IP.
• Protect the underlying technology. All platform code, agent architecture, prompt engineering, workflow automations, and AI models remain Provider's exclusive property. The data portability provisions only cover client-specific outputs and configurations.
• Performance milestones must be conditioned on client obligations. Never commit to outcomes that depend on client actions (ad spend, content publishing) without conditioning the milestone on the client fulfilling those obligations.
• ROI claims must be credible. Use revenue opportunity framing. Never use specific multipliers. Let the math speak for itself.
• Content volume = capacity, not commitment. Frame as what the agent can do, with practical quality-controlled targets.
• Governing law should favor the client's state as a good-faith gesture, unless the user specifies otherwise.
• Brand styling: Primary color 1E2761 (navy), accent 4472C4 (blue). Font: Georgia for headings, Calibri for body. US Letter page size with 1-inch margins.

Step 4: Customize Performance Milestones

Performance milestones must be tailored to the specific engagement. For each milestone:

1. Define the metric — What is being measured (traffic, leads, content published, etc.)
2. Set a conservative threshold — Should be easily achievable if both parties perform; set at ~50% of realistic expectations
3. Define the client obligation — What must the client do for this milestone to apply
4. Define the remedy — What happens if missed (remediation plan, termination right, refund)

Example Milestone Structure (Marketing Agent)

Timeframe	Milestone	Client Obligation	Remedy
Month 3	75+ content pages published and indexed	Client publishes 80%+ of delivered content within 5 business days	Remediation plan within 10 days
Month 4	PPC campaigns live, 1,000+ impressions/mo	Client maintains $3K/mo minimum ad spend	Remediation plan within 10 days
Month 6	750 organic visits/mo OR 3 qualified leads/mo	Client maintained all obligations for preceding 3 months	Client may terminate; pro-rated build refund
Month 9	1,500 organic visits/mo AND 5 qualified leads/mo	All obligations maintained continuously	Remediation plan; good-faith discussion
Month 12	3,000 organic visits/mo	All obligations maintained continuously	No auto-renewal if missed

For non-marketing agents (estimation, personnel, operations), adjust milestones to the relevant KPIs (e.g., estimate turnaround time, hire-to-start time, error rates).

Step 5: Deliver

1. Generate the .docx using the process above
2. Tell the user where the file was saved
3. Offer to adjust any section before sending to the client
4. Offer to generate a companion slide deck if needed (reference the ruh-proposal skill)

Dependencies

• python-docx Python package (python3 -m pip install python-docx if not already installed)
• Python 3
• The reference structure at references/msa-structure.md