Product Documentation Modernization Skill

Version: 1.0.0 Created: 2026-01-08 Category: Documentation, Product Management, Standards Compliance

Overview

When to Use

• Initializing Agent OS product documentation for new repositories
• Reviewing existing product documentation for improvements
• Ensuring compliance with workspace-hub standards (UV, Plotly, file organization)
• Adding quantifiable metrics and success criteria to product documents
• Modernizing technology stacks to current best practices
• Documenting modular architecture decisions

Skill Components

1. Mission Document Review & Enhancement

• Includes quantifiable claim (e.g., "reduces overhead by 70%")
• Clearly states target users and specific pain point
• Explains value proposition in one sentence
• Uses active, benefit-focused language

• Includes age range and role
• Defines business context (number of projects, team size, etc.)
• Lists specific, measurable pain points with time/cost impacts
• States concrete goals with success criteria

**Business Administrator** (28-45 years old)
- **Role:** Administrative Manager or Business Operations Coordinator
- **Context:** Day-to-day management of business finances, invoicing, and compliance for 3-7 concurrent engineering projects
- **Pain Points:**
  - Spending 6-8 hours/week on invoice generation across multiple clients
  - Manual expense categorization from credit card statements (2-3 hours/week)
  - Annual tax preparation requires 20-30 hours of document organization
- **Goals:**
  - Reduce administrative time by 70% to focus on business development
  - Achieve 100% on-time invoice delivery (currently 75%)

• Each feature includes impact metrics or time savings
• Features grouped by category (Core, Collaboration, Integration)
• Features written from user benefit perspective, not technical implementation

• Efficiency Gains: Specific time reductions (e.g., 85% reduction in invoice time)
• Business Impact: Dollar savings (e.g., $15K-25K annually)
• Adoption Success: Timeline and satisfaction metrics
• All metrics are measurable and achievable

• Phased approach with clear timelines
• Each phase shows immediate value delivery
• Zero business disruption strategy
• Manual override availability

2. Tech Stack Modernization

• Uses UV package manager (workspace-hub standard) - NOT Conda/Poetry
• Python 3.11+ specified with modern type hints
• All dependencies use current major versions (e.g., Pandas 2.0+, not 1.x)
• Deprecated libraries replaced (e.g., pypdf instead of PyPDF2)

• Plotly MANDATORY for all visualizations
• Explicit note: "All visualizations MUST be interactive (Plotly)"
• NO Matplotlib, seaborn, or static image exports
• Kaleido for static exports FROM interactive Plotly charts only

• Reflects decisions.md modular design (e.g., DEC-003)
• Each module has clear CLI command (e.g.,

  invoice-gen

  ,

  tax-prep

  )
• Shared components explicitly listed
• Module boundaries clearly defined

• Full pyproject.toml configuration included
• All categories covered: data processing, document generation, visualization, email, automation, logging, CLI, testing
• Development dependencies separated (

  [project.optional-dependencies]

  )
• Entry point scripts defined (

  [project.scripts]

  )

• Click or Typer framework specified
• Command examples for each module
• Option documentation included
• Usage patterns demonstrated

• Coverage requirements specified (minimum 80%, critical modules 95%)
• Test structure documented (unit/, integration/, performance/)
• Testing commands provided

• UV installation instructions
• Virtual environment creation steps
• Cross-platform support (Windows/macOS/Linux)
• Editor recommendations

3. Standards Compliance Verification

# ✅ Correct
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install -e .

# ❌ Wrong
conda create -n myenv
pip install -r requirements.txt

# ✅ Correct - Plotly interactive
import plotly.express as px
fig = px.scatter(df, x='time', y='value')
fig.write_html('../reports/analysis.html')

# ❌ Wrong - Matplotlib static
import matplotlib.pyplot as plt
plt.scatter(df['time'], df['value'])
plt.savefig('plot.png')

• Reports in

  /reports/

  directory
• Data in

  /data/

  (raw/, processed/, results/)
• No files saved to root folder
• Module-based source organization in

  /src/

• Uses relative paths from report location
• No hardcoded absolute paths
• Standardized data directory structure

4. Quantification Framework

Before: 15 minutes per invoice × 10 invoices/month = 150 minutes/month
After: 2 minutes per invoice × 10 invoices/month = 20 minutes/month
Reduction: 130 minutes/month = 87% time savings

Hourly rate: $75/hour
Time saved: 130 minutes/month × 12 months = 1,560 minutes/year = 26 hours/year
Value: 26 hours × $75 = $1,950/year per use case

Total across 3 use cases: ~$5,850/year
Add accountant fee reduction: $2,000-5,000/year
Total: $15,000-25,000/year

Week 1-2: Initial setup and first automated invoice
Week 3-4: Expense tracking automation
Week 5-8: Full tax preparation integration
Result: 8 weeks to full adoption

5. Engineering-Specific Differentiation

• Project-based billing emphasized
• Technical hours tracking mentioned
• Multi-client parallel project management
• Engineering service-specific expense categories (certifications, software licenses, standards)
• Professional engineering compliance tracking

### Engineering Project Financial Tracking

Unlike generic accounting systems, we provide project-based billing with technical hours tracking, multi-client parallel project management, and engineering service-specific expense categorization (design software, certifications, industry standards). This results in accurate project profitability analysis and improved resource allocation for engineering teams.

Implementation Process

Step 1: Read Current Documentation

# Read all three product documents
cat .agent-os/product/mission.md
cat .agent-os/product/tech-stack.md
cat .agent-os/product/decisions.md

Step 2: Review Against Standards

• Compare against workspace-hub standards
• Check for deprecated technologies
• Verify quantifiable metrics exist
• Ensure modular architecture documented

Step 3: Suggest Improvements

• Organize suggestions by category
• Prioritize based on impact
• Provide specific examples
• Include rationale for each change

Step 4: Implement Changes

• Use Edit operations for precision
• Update version numbers and dates
• Maintain document structure
• Cross-reference with decisions.md

Step 5: Validate Compliance

• Verify UV package manager used
• Confirm Plotly for all visualizations
• Check modular architecture alignment
• Ensure quantifiable metrics included

Templates

Mission.md Success Metrics Template

## Success Metrics

### Efficiency Gains
- **[Feature]:** [%] reduction in time ([before] → [after])
- **[Feature]:** [%] reduction in [metric] ([before] → [after])

### Business Impact
- **Cost Savings:** $[amount] annually ([breakdown])
- **Revenue Protection:** $[amount] in [area]
- **Risk Reduction:** [%] accuracy improvement

### Adoption Success
- **Time to First Value:** [timeframe]
- **Full System Adoption:** [timeframe]
- **User Satisfaction:** [measurable outcome]

Tech-Stack.md pyproject.toml Template

[project]
name = "project-name"
version = "1.0.0"
description = "Brief description"
requires-python = ">=3.11"
dependencies = [
    # Data Processing
    "pandas>=2.0.0",
    "numpy>=1.24.0",

    # Visualization (Interactive Only)
    "plotly>=5.14.0",
    "kaleido>=0.2.1",

    # CLI Development
    "click>=8.1.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=7.4.0",
    "pytest-cov>=4.1.0",
    "ruff>=0.1.0",
]

[project.scripts]
module-name = "package.module:main"

Example Usage

Review Mission Document

# In Claude Code or AI agent
"Review the mission.md file and suggest improvements following the Product Documentation Modernization skill. Focus on adding quantifiable metrics and engineering-specific value propositions."

Modernize Tech Stack

# In Claude Code or AI agent
"Review tech-stack.md for compliance with workspace-hub standards. Replace Conda with UV, ensure Plotly is mandatory, and add complete pyproject.toml configuration."

Success Criteria

• Includes 3+ quantifiable efficiency gains
• Contains dollar-value business impact metrics
• Has complete Success Metrics section
• Includes Implementation Approach section
• Features engineering-specific differentiation

• Uses UV package manager (not Conda)
• Plotly mandatory with explicit note
• Complete pyproject.toml included
• Modular architecture documented
• CLI commands for all modules
• Testing strategy with coverage requirements
• Development environment setup included

• Version updated (e.g., 1.0.0 → 2.0.0)
• Date updated to current
• Cross-referenced with decisions.md
• No deprecated technologies
• No workspace-hub standard violations

Related Skills

• File Organization Skill - For organizing documentation and code files
• Standards Compliance Skill - For verifying workspace-hub standards
• Quantification Skill - For calculating time and cost savings
• Agent OS Initialization Skill - For setting up new repositories

References

• Workspace-Hub Standards:

  @/mnt/github/workspace-hub/docs/modules/standards/

• Agent OS Instructions:

  @~/.agent-os/instructions/

• UV Package Manager: https://github.com/astral-sh/uv
• Plotly Documentation: https://plotly.com/python/

Version History

• 1.0.0 (2026-01-08): Initial skill creation based on aceengineer-admin mission.md and tech-stack.md modernization work