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docs: refresh product team guidance and plugin metadata

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2026-03-08 15:36:32 +01:00
committed by Reza Rezvani
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product-team/.claude-plugin/plugin.json
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@@ -1,6 +1,6 @@
{
"name": "product-skills",
"description": "8 product skills: product manager toolkit (RICE, PRDs), agile product owner, product strategist, UX researcher designer, UI design system, competitive teardown, landing page generator, and SaaS scaffolder",
"description": "12 production-ready product skills: product manager toolkit (RICE, PRDs), agile product owner, product strategist, UX researcher, UI design system, competitive teardown, landing page generator, SaaS scaffolder, product analytics, experiment designer, product discovery, and roadmap communicator",
"version": "2.1.2",
"author": {
"name": "Alireza Rezvani",

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product-team/CLAUDE.md
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@@ -1,6 +1,6 @@
# Product Team Skills - Claude Code Guidance
This guide covers the 8 production-ready product management skills and their Python automation tools.
This guide covers the 12 production-ready product management skills and their Python automation tools.
## Product Skills Overview
@@ -13,12 +13,16 @@ This guide covers the 8 production-ready product management skills and their Pyt
6. **competitive-teardown/** - Competitive matrix building, gap analysis (1 tool)
7. **landing-page-generator/** - Landing page scaffolding (1 tool)
8. **saas-scaffolder/** - SaaS project bootstrapping (1 tool)
9. **product-analytics/** - KPI design, retention/cohort/funnel analysis (1 tool)
10. **experiment-designer/** - Experiment design and sample size planning (1 tool)
11. **product-discovery/** - Discovery frameworks and assumption mapping (1 tool)
12. **roadmap-communicator/** - Roadmap communication and changelog generation (1 tool)
**Total Tools:** 9 Python automation tools
**Total Tools:** 13 Python automation tools
**Agents:** 4 (cs-product-manager, cs-agile-product-owner, cs-product-strategist, cs-ux-researcher)
**Agents:** 5 (cs-product-manager, cs-agile-product-owner, cs-product-strategist, cs-ux-researcher, cs-product-analyst)
**Slash Commands:** 5 (/rice, /okr, /persona, /user-story, /competitive-matrix)
**Slash Commands:** 7 (/rice, /okr, /persona, /user-story, /competitive-matrix, /prd, /sprint-plan)
## Python Automation Tools
@@ -95,14 +99,6 @@ python agile-product-owner/scripts/user_story_generator.py
python agile-product-owner/scripts/user_story_generator.py sprint 30
```
**Output Format:**
```
US-001: As a user, I want to...
Priority: High | Points: 5
Acceptance Criteria:
- Given... When... Then...
```
### 4. OKR Cascade Generator (`product-strategist/scripts/okr_cascade_generator.py`)
**Purpose:** Automated OKR hierarchy (company → product → team)
@@ -126,18 +122,9 @@ python product-strategist/scripts/okr_cascade_generator.py retention
**Purpose:** Data-driven persona creation from user research
**Features:**
- Demographic and psychographic profiling
- Goals, pain points, and behavior patterns
- User journey mapping integration
- Empathy map generation
**Usage:**
```bash
# Interactive persona creation
python ux-researcher-designer/scripts/persona_generator.py
# JSON export
python ux-researcher-designer/scripts/persona_generator.py --output json
```
@@ -145,22 +132,10 @@ python ux-researcher-designer/scripts/persona_generator.py --output json
**Purpose:** Complete design token system from brand color
**Features:**
- Color palette generation (primary, secondary, neutrals)
- Typography scale (font sizes, line heights, weights)
- Spacing system (4px/8px grid)
- Shadow and elevation tokens
- Export formats: CSS, JSON, SCSS
**Usage:**
```bash
# Generate design tokens
python ui-design-system/scripts/design_token_generator.py "#0066CC" modern css
# SCSS output
python ui-design-system/scripts/design_token_generator.py "#0066CC" modern scss
# JSON for Figma integration
python ui-design-system/scripts/design_token_generator.py "#0066CC" modern json
```
@@ -182,47 +157,11 @@ python competitive-teardown/scripts/competitive_matrix_builder.py competitors.js
- 4 design styles: `dark-saas`, `clean-minimal`, `bold-startup`, `enterprise`
- 7 section generators: nav, hero, features, testimonials, pricing, CTA, footer
- Copy frameworks: PAS, AIDA, BAB
- SEO metadata export
- HTML output preserved via `--format html`
**Usage:**
```bash
# TSX output (default) with design style
python landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx
# HTML output
python landing-page-generator/scripts/landing_page_scaffolder.py config.json --format html
# JSON manifest (dry run)
python landing-page-generator/scripts/landing_page_scaffolder.py config.json --format json
```
**Config JSON format:**
```json
{
"product_name": "Acme",
"tagline": "Ship faster. Break less.",
"design_style": "dark-saas",
"copy_framework": "PAS",
"sections": ["nav", "hero", "features", "pricing", "cta", "footer"],
"features": [
{"title": "Fast deploys", "description": "Zero-downtime deployments"}
],
"pricing": [
{"name": "Free", "price": "$0/mo", "features": ["5 projects"]},
{"name": "Pro", "price": "$29/mo", "features": ["Unlimited"], "highlighted": true}
]
}
```
**Brand Voice Integration:** Before generating copy, run the brand voice analyzer to establish tone and formality:
```bash
# 1. Analyze existing brand content to establish voice profile
python ../marketing-skill/content-production/scripts/brand_voice_analyzer.py brand_samples.txt --format json > voice_profile.json
# 2. Use the voice profile (formality, tone, perspective) to guide copy framework selection
# 3. Generate landing page with matching style
python landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx
```
### 9. Project Bootstrapper (`saas-scaffolder/scripts/project_bootstrapper.py`)
@@ -234,102 +173,123 @@ python landing-page-generator/scripts/landing_page_scaffolder.py config.json --f
python saas-scaffolder/scripts/project_bootstrapper.py project_config.json
```
### 10. Metrics Calculator (`product-analytics/scripts/metrics_calculator.py`)
**Purpose:** Product analytics — retention, cohort, and funnel analysis
**Features:**
- Retention curve analysis from event data
- Funnel conversion tracking with stage-by-stage drop-off
- Cohort grouping and comparison
**Usage:**
```bash
# Retention analysis
python product-analytics/scripts/metrics_calculator.py retention events.csv
# Funnel analysis
python product-analytics/scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay
# KPI summary
python product-analytics/scripts/metrics_calculator.py kpi metrics.csv --json
```
### 11. Sample Size Calculator (`experiment-designer/scripts/sample_size_calculator.py`)
**Purpose:** Statistical sample size planning for A/B tests and experiments
**Features:**
- Minimum detectable effect (MDE) calculation
- Absolute and relative effect size modes
- Power analysis with configurable alpha/beta
**Usage:**
```bash
# Absolute MDE
python experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute
# Relative MDE
python experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.15 --mde-type relative
# Custom power/significance
python experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --alpha 0.01 --power 0.9
```
### 12. Assumption Mapper (`product-discovery/scripts/assumption_mapper.py`)
**Purpose:** Map and prioritize product assumptions for discovery validation
**Features:**
- Risk × uncertainty scoring for prioritization
- CSV input with structured assumption fields
- Categorization by assumption type (desirability, viability, feasibility, usability)
**Usage:**
```bash
python product-discovery/scripts/assumption_mapper.py assumptions.csv
python product-discovery/scripts/assumption_mapper.py assumptions.csv --json
```
### 13. Changelog Generator (`roadmap-communicator/scripts/changelog_generator.py`)
**Purpose:** Generate structured changelogs from git commit history
**Note:** Requires `git` on PATH — must be run inside a git repository.
**Usage:**
```bash
python roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to HEAD
python roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to v2.0.0 --json
```
## Product Workflows
### Workflow 1: Feature Prioritization
### Workflow 1: Feature Prioritization to Sprint Execution
```bash
# 1. Collect feature requests
cat feature-requests.csv
# 2. Run RICE prioritization
python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 30
# 3. Generate quarterly roadmap
# 4. Create user stories for top priorities
python agile-product-owner/scripts/user_story_generator.py sprint 30
```
### Workflow 2: User Research to Product
### Workflow 2: Strategy to Team-Level OKRs
```bash
# 1. Conduct user interviews
# 2. Analyze transcripts
python product-manager-toolkit/scripts/customer_interview_analyzer.py interview-001.txt
# 3. Generate personas
python ux-researcher-designer/scripts/persona_generator.py
# 4. Create OKRs based on insights
python product-strategist/scripts/okr_cascade_generator.py growth
python product-strategist/scripts/okr_cascade_generator.py growth --json > okrs.json
```
### Workflow 3: Sprint Planning
### Workflow 3: Research to Persona Artifacts
```bash
# 1. Set sprint capacity (story points)
CAPACITY=30
# 2. Generate user stories
python agile-product-owner/scripts/user_story_generator.py sprint $CAPACITY
# 3. Export to Jira (via JSON)
python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json > priorities.json
python ux-researcher-designer/scripts/persona_generator.py json > personas.json
```
### Workflow 4: Brand-Aligned Landing Page
This workflow connects the marketing brand voice skill with the landing page generator to ensure copy consistency.
```bash
# 1. Analyze existing brand content for voice profile
python ../marketing-skill/content-production/scripts/brand_voice_analyzer.py website_copy.txt --format json > voice.json
# Output: formality (formal/casual), tone (professional/friendly), perspective (authoritative/conversational)
# 2. Map voice profile to design style + copy framework:
# - formal + professional → enterprise style, AIDA framework
# - casual + friendly → bold-startup style, BAB framework
# - professional + authoritative → dark-saas style, PAS framework
# - casual + conversational → clean-minimal style, BAB framework
# 3. Generate design tokens for brand consistency
python ui-design-system/scripts/design_token_generator.py "#0066CC" modern css
# 4. Generate the landing page
python landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx
# 5. Run competitive teardown to refine positioning
python competitive-teardown/scripts/competitive_matrix_builder.py competitors.json
```
## Integration Patterns
### Jira Integration
All tools support JSON output for Jira import:
### Workflow 5: Product Analytics and Experimentation
```bash
# Export prioritized features
python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json > jira-import.json
python product-analytics/scripts/metrics_calculator.py retention events.csv
python product-analytics/scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay
python experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute
```
### Figma Integration
Design tokens export for Figma plugins:
### Workflow 6: Discovery and Opportunity Validation
```bash
# Generate tokens
python ui-design-system/scripts/design_token_generator.py "#0066CC" modern json > design-tokens.json
python product-discovery/scripts/assumption_mapper.py assumptions.csv
```
### Confluence Documentation
Use persona generator output for user documentation:
### Workflow 7: Roadmap and Release Communication
```bash
python ux-researcher-designer/scripts/persona_generator.py --output json > personas.json
python roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to HEAD
```
## Quality Standards
@@ -341,20 +301,6 @@ python ux-researcher-designer/scripts/persona_generator.py --output json > perso
- Standard library only (minimal dependencies)
- Actionable recommendations
## Cross-Domain Integration
### Brand Voice → Landing Page
The landing page generator integrates with the marketing brand voice analyzer (`marketing-skill/content-production/scripts/brand_voice_analyzer.py`) to ensure copy on generated pages matches the brand's established voice. The analyzer outputs formality, tone, and perspective dimensions which map to design style and copy framework choices. See Workflow 4 above.
### Design Tokens → Landing Page
Design tokens from `ui-design-system/scripts/design_token_generator.py` can be generated alongside landing pages to ensure consistent color, typography, and spacing across the product.
### Competitive Teardown → Landing Page
Competitive positioning from `competitive-teardown/scripts/competitive_matrix_builder.py` informs landing page messaging — use SWOT analysis to identify differentiation points and translate them into hero copy and feature sections.
## Additional Resources
- **Main Documentation:** `../CLAUDE.md`
@@ -362,7 +308,7 @@ Competitive positioning from `competitive-teardown/scripts/competitive_matrix_bu
---
**Last Updated:** March 10, 2026
**Skills Deployed:** 8/8 product skills production-ready
**Total Tools:** 9 Python automation tools
**Agents:** 4 | **Commands:** 5
**Last Updated:** March 11, 2026
**Skills Deployed:** 12/12 product skills production-ready
**Total Tools:** 13 Python automation tools
**Agents:** 5 | **Commands:** 7