agent-management
Create, manage, and orchestrate AI agents using the AI Maestro CLI. Use when the user asks to "create agent", "list agents",…
Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy
Claude Code
$ npx -y skills add davila7/claude-code-templates --skill product-manager-toolkit --agent claude-code
Codex
$ npx skills add davila7/claude-code-templates --skill product-manager-toolkit -a codex -y
Cursor
$ npx skills add davila7/claude-code-templates --skill product-manager-toolkit -a cursor -y
Gemini CLI
$ npx skills add davila7/claude-code-templates --skill product-manager-toolkit -a gemini-cli -y
GitHub Copilot
$ npx skills add davila7/claude-code-templates --skill product-manager-toolkit -a github-copilot -y
OpenCode
$ npx skills add davila7/claude-code-templates --skill product-manager-toolkit -a opencode -y
Windsurf
$ npx skills add davila7/claude-code-templates --skill product-manager-toolkit -a windsurf -y
name: product-manager-toolkit description: Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.
Essential tools and frameworks for modern product management, from discovery to delivery.
python scripts/rice_prioritizer.py sample # Create sample CSV python scripts/rice_prioritizer.py sample_features.csv --capacity 15
python scripts/customer_interview_analyzer.py interview_transcript.txt
1. Choose template from `references/prd_templates.md` 2. Fill in sections based on discovery work 3. Review with stakeholders 4. Version control in your PM tool
1. **Gather Feature Requests**
2. **Score with RICE**
# Create CSV with: name,reach,impact,confidence,effort python scripts/rice_prioritizer.py features.csv
3. **Analyze Portfolio**
4. **Generate Roadmap**
1. **Conduct Interviews**
2. **Analyze Insights**
python scripts/customer_interview_analyzer.py transcript.txt
Extracts:
3. **Synthesize Findings**
4. **Validate Solutions**
1. **Choose Template**
2. **Structure Content**
3. **Collaborate**
Advanced RICE framework implementation with portfolio analysis.
**Features**:
**Usage Examples**:
# Basic prioritization python scripts/rice_prioritizer.py features.csv # With custom team capacity (person-months per quarter) python scripts/rice_prioritizer.py features.csv --capacity 20 # Output as JSON for integration python scripts/rice_prioritizer.py features.csv --output json
NLP-based interview analysis for extracting actionable insights.
**Capabilities**:
**Usage Examples**:
# Analyze single interview python scripts/customer_interview_analyzer.py interview.txt # Output as JSON for aggregation python scripts/customer_interview_analyzer.py interview.txt json
Multiple PRD formats for different contexts:
1. **Standard PRD Template**
2. **One-Page PRD**
3. **Agile Epic Template**
4. **Feature Brief**
Score = (Reach × Impact × Confidence) / Effort Reach: # of users/quarter Impact: - Massive = 3x - High = 2x - Medium = 1x - Low = 0.5x - Minimal = 0.25x Confidence: - High = 100% - Medium = 80% - Low = 50% Effort: Person-months
Low Effort High Effort
High QUICK WINS BIG BETS
Value [Prioritize] [Strategic]
Low FILL-INS TIME SINKS
Value [Maybe] [Avoid]1. Context Questions (5 min) - Role and responsibilities - Current workflow - Tools used 2. Problem Exploration (15 min) - Pain points - Frequency and impact - Current workarounds 3. Solution Validation (10 min) - Reaction to concepts - Value perception - Willingness to pay 4. Wrap-up (5 min) - Other thoughts - Referrals - Follow-up permission
We believe that [building this feature] For [these users] Will [achieve this outcome] We'll know we're right when [metric]
Outcome ├── Opportunity 1 │ ├── Solution A │ └── So
Open-source registry and CLI for Claude Code components: agents, commands, skills, hooks, MCPs, settings and mods
Create, manage, and orchestrate AI agents using the AI Maestro CLI. Use when the user asks to "create agent", "list agents",…
Send and receive cryptographically signed messages between AI agents using the Agent Messaging Protocol (AMP). Use when the user…
Search auto-generated codebase documentation for function signatures, API docs, class definitions, and code comments. Use when…
Query the code graph database to understand component relationships, dependencies, and change impact. Use when the user asks to…
Search conversation history and semantic memory to recall previous discussions, decisions, and context. Use when the user asks to…
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…
Ask which skill or flow fits your situation. A router over the skills in this repo.