product-documentation-1-mission-document-review-enhancement
Sub-skill of product-documentation: 1. Mission Document Review & Enhancement (+4).
Best use case
product-documentation-1-mission-document-review-enhancement is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of product-documentation: 1. Mission Document Review & Enhancement (+4).
Teams using product-documentation-1-mission-document-review-enhancement should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/1-mission-document-review-enhancement/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How product-documentation-1-mission-document-review-enhancement Compares
| Feature / Agent | product-documentation-1-mission-document-review-enhancement | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of product-documentation: 1. Mission Document Review & Enhancement (+4).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 1. Mission Document Review & Enhancement (+4)
## 1. Mission Document Review & Enhancement
**Checklist for mission.md:**
**Pitch Section:**
- [ ] 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
**User Personas:**
- [ ] 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
**Example:**
```markdown
**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%)
```
**Key Features:**
- [ ] Each feature includes impact metrics or time savings
- [ ] Features grouped by category (Core, Collaboration, Integration)
- [ ] Features written from user benefit perspective, not technical implementation
**Success Metrics Section (Required):**
- [ ] 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
**Implementation Approach Section (Required):**
- [ ] Phased approach with clear timelines
- [ ] Each phase shows immediate value delivery
- [ ] Zero business disruption strategy
- [ ] Manual override availability
## 2. Tech Stack Modernization
**Checklist for tech-stack.md:**
**Core Technologies:**
- [ ] 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)
**Visualization Standards:**
- [ ] 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
**Modular Architecture:**
- [ ] 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
**Complete Dependencies:**
- [ ] 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]`)
**CLI Interface:**
- [ ] Click or Typer framework specified
- [ ] Command examples for each module
- [ ] Option documentation included
- [ ] Usage patterns demonstrated
**Testing Strategy:**
- [ ] Coverage requirements specified (minimum 80%, critical modules 95%)
- [ ] Test structure documented (unit/, integration/, performance/)
- [ ] Testing commands provided
**Development Environment:**
- [ ] UV installation instructions
- [ ] Virtual environment creation steps
- [ ] Cross-platform support (Windows/macOS/Linux)
- [ ] Editor recommendations
## 3. Standards Compliance Verification
**Workspace-Hub Standards:**
**UV Package Manager:**
```bash
# ✅ 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
```
**Interactive Visualizations:**
```python
# ✅ 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')
```
**File Organization:**
- [ ] Reports in `/reports/` directory
- [ ] Data in `/data/` (raw/, processed/, results/)
- [ ] No files saved to root folder
- [ ] Module-based source organization in `/src/`
**CSV Data Import:**
- [ ] Uses relative paths from report location
- [ ] No hardcoded absolute paths
- [ ] Standardized data directory structure
## 4. Quantification Framework
**Adding Metrics to Documents:**
**Time Savings Calculation:**
```
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
```
**Cost Savings Calculation:**
```
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
```
**Adoption Timeline:**
```
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
**For Engineering Firms:**
- [ ] 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
**Example Differentiator:**
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