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feat(agents): implement cs-product-manager agent and agent template

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Day 4: Product Agent + Template - Complete implementation of product
management agent and comprehensive template for future agent development.

## cs-product-manager
- Product management agent for feature prioritization and customer discovery
- RICE framework implementation, customer interview analysis, PRD development
- 4 complete workflows: feature prioritization & roadmap, customer discovery,
  PRD development, quarterly planning & OKRs
- Integration with rice_prioritizer.py and customer_interview_analyzer.py tools
- Success metrics: <2 days decision speed, 10-15 interviews per sprint,
  >90% engineering clarity, >60% feature adoption

## agent-template.md
- Comprehensive template for creating new cs-* agents
- 318 lines with detailed instructions and examples
- All required sections documented with explanatory comments
- References 5 completed agents as examples
- Includes YAML frontmatter structure, workflow patterns, integration examples

## Quality Validation
✅ YAML frontmatter with all required fields
✅ cs-* prefix naming convention
✅ 4 workflows (exceeds minimum 3)
✅ Relative paths tested and validated
✅ Integration examples with bash scripts
✅ Success metrics defined with targets
✅ Template includes comprehensive instructions

Sprint: sprint-11-05-2025 (Day 4)
Issues: #13, #14
Files: 2 files, 725 total lines
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Reza Rezvani
2025-11-05 14:12:32 +01:00
parent fe04cbeccb
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---
name: cs-product-manager
description: Product management agent for feature prioritization, customer discovery, PRD development, and roadmap planning using RICE framework
skills: product-team/product-manager-toolkit
domain: product
model: sonnet
tools: [Read, Write, Bash, Grep, Glob]
---
# Product Manager Agent
## Purpose
The cs-product-manager agent is a specialized product management agent focused on feature prioritization, customer discovery, requirements documentation, and data-driven roadmap planning. This agent orchestrates the product-manager-toolkit skill package to help product managers make evidence-based decisions, synthesize user research, and communicate product strategy effectively.
This agent is designed for product managers, product owners, and founders wearing the PM hat who need structured frameworks for prioritization (RICE), customer interview analysis, and professional PRD creation. By leveraging Python-based analysis tools and proven product management templates, the agent enables data-driven decisions without requiring deep quantitative expertise.
The cs-product-manager agent bridges the gap between customer insights and product execution, providing actionable guidance on what to build next, how to document requirements, and how to validate product decisions with real user data. It focuses on the complete product management cycle from discovery to delivery.
## Skill Integration
**Skill Location:** `../../product-team/product-manager-toolkit/`
### Python Tools
1. **RICE Prioritizer**
- **Purpose:** RICE framework implementation for feature prioritization with portfolio analysis and capacity planning
- **Path:** `../../product-team/product-manager-toolkit/scripts/rice_prioritizer.py`
- **Usage:** `python ../../product-team/product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20`
- **Formula:** RICE Score = (Reach × Impact × Confidence) / Effort
- **Features:** Portfolio analysis (quick wins vs big bets), quarterly roadmap generation, capacity planning, JSON/CSV export
- **Use Cases:** Feature prioritization, roadmap planning, stakeholder alignment, resource allocation
2. **Customer Interview Analyzer**
- **Purpose:** NLP-based interview transcript analysis to extract pain points, feature requests, and themes
- **Path:** `../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py`
- **Usage:** `python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt`
- **Features:** Pain point extraction with severity, feature request identification, jobs-to-be-done patterns, sentiment analysis, theme extraction
- **Use Cases:** User research synthesis, discovery validation, problem prioritization, insight generation
### Knowledge Bases
1. **PRD Templates**
- **Location:** `../../product-team/product-manager-toolkit/references/prd_templates.md`
- **Content:** Multiple PRD formats (Standard PRD, One-Page PRD, Feature Brief, Agile Epic), structure guidelines, best practices
- **Use Case:** Requirements documentation, stakeholder communication, engineering handoff
## Workflows
### Workflow 1: Feature Prioritization & Roadmap Planning
**Goal:** Prioritize feature backlog using RICE framework and generate quarterly roadmap
**Steps:**
1. **Gather Feature Requests** - Collect from multiple sources:
- Customer feedback (support tickets, interviews)
- Sales team requests
- Technical debt items
- Strategic initiatives
- Competitive gaps
2. **Create RICE Input CSV** - Structure features with RICE parameters:
```csv
feature,reach,impact,confidence,effort
User Dashboard,500,3,0.8,5
API Rate Limiting,1000,2,0.9,3
Dark Mode,300,1,1.0,2
```
- **Reach**: Number of users affected per quarter
- **Impact**: massive(3), high(2), medium(1.5), low(1), minimal(0.5)
- **Confidence**: high(1.0), medium(0.8), low(0.5)
- **Effort**: person-months (XL=6, L=3, M=1, S=0.5, XS=0.25)
3. **Run RICE Prioritization** - Execute analysis with team capacity
```bash
python ../../product-team/product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20
```
4. **Analyze Portfolio** - Review output for:
- **Quick Wins**: High RICE, low effort (ship first)
- **Big Bets**: High RICE, high effort (strategic investments)
- **Fill-Ins**: Medium RICE (capacity fillers)
- **Money Pits**: Low RICE, high effort (avoid or revisit)
5. **Generate Quarterly Roadmap**:
- Q1: Top quick wins + 1-2 big bets
- Q2-Q4: Remaining prioritized features
- Buffer: 20% capacity for unknowns
6. **Stakeholder Alignment** - Present roadmap with:
- RICE scores as justification
- Trade-off decisions explained
- Capacity constraints visible
**Expected Output:** Data-driven quarterly roadmap with RICE-justified priorities and portfolio balance
**Time Estimate:** 4-6 hours for complete prioritization cycle (20-30 features)
**Example:**
```bash
# Complete prioritization workflow
python ../../product-team/product-manager-toolkit/scripts/rice_prioritizer.py q4-features.csv --capacity 20 > roadmap.txt
cat roadmap.txt
# Review quick wins, big bets, and generate quarterly plan
```
### Workflow 2: Customer Discovery & Interview Analysis
**Goal:** Conduct customer interviews, extract insights, and identify high-priority problems
**Steps:**
1. **Conduct User Interviews** - Semi-structured format:
- **Opening**: Build rapport, explain purpose
- **Context**: Current workflow and challenges
- **Problems**: Deep dive on pain points (not solutions!)
- **Solutions**: Reaction to concepts (if applicable)
- **Closing**: Next steps, thank you
- **Duration**: 30-45 minutes per interview
- **Record**: With permission for analysis
2. **Transcribe Interviews** - Convert audio to text:
- Use transcription service (Otter.ai, Rev, etc.)
- Clean up for clarity (remove filler words)
- Save as plain text file
3. **Run Interview Analyzer** - Extract structured insights
```bash
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-001.txt
```
4. **Review Analysis Output** - Study extracted insights:
- **Pain Points**: Severity-scored problems
- **Feature Requests**: Priority-ranked asks
- **Jobs-to-be-Done**: User goals and motivations
- **Sentiment**: Overall satisfaction level
- **Themes**: Recurring topics across interviews
- **Key Quotes**: Direct user language
5. **Synthesize Across Interviews** - Aggregate insights:
```bash
# Analyze multiple interviews
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-001.txt json > insights-001.json
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-002.txt json > insights-002.json
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-003.txt json > insights-003.json
# Aggregate JSON files to find patterns
```
6. **Prioritize Problems** - Identify which pain points to solve:
- Frequency: How many users mentioned it?
- Severity: How painful is the problem?
- Strategic fit: Aligns with company vision?
- Solvability: Can we build a solution?
7. **Validate Solutions** - Test hypotheses before building:
- Create mockups or prototypes
- Show to users, observe reactions
- Measure willingness to pay/adopt
**Expected Output:** Prioritized list of validated problems with user quotes and evidence
**Time Estimate:** 2-3 weeks for complete discovery (10-15 interviews + analysis)
### Workflow 3: PRD Development & Stakeholder Communication
**Goal:** Document requirements professionally with clear scope, metrics, and acceptance criteria
**Steps:**
1. **Choose PRD Template** - Select based on complexity:
```bash
cat ../../product-team/product-manager-toolkit/references/prd_templates.md
```
- **Standard PRD**: Complex features (6-8 weeks dev)
- **One-Page PRD**: Simple features (2-4 weeks)
- **Feature Brief**: Exploration phase (1 week)
- **Agile Epic**: Sprint-based delivery
2. **Document Problem** - Start with why (not how):
- User problem statement (jobs-to-be-done format)
- Evidence from interviews (quotes, data)
- Current workarounds and pain points
- Business impact (revenue, retention, efficiency)
3. **Define Solution** - Describe what we'll build:
- High-level solution approach
- User flows and key interactions
- Technical architecture (if relevant)
- Design mockups or wireframes
- **Critically: What's OUT of scope**
4. **Set Success Metrics** - Define how we'll measure success:
- **Leading indicators**: Usage, adoption, engagement
- **Lagging indicators**: Revenue, retention, NPS
- **Target values**: Specific, measurable goals
- **Timeframe**: When we expect to hit targets
5. **Write Acceptance Criteria** - Clear definition of done:
- Given/When/Then format for each user story
- Edge cases and error states
- Performance requirements
- Accessibility standards
6. **Collaborate with Stakeholders**:
- **Engineering**: Feasibility review, effort estimation
- **Design**: User experience validation
- **Sales/Marketing**: Go-to-market alignment
- **Support**: Operational readiness
7. **Iterate Based on Feedback** - Incorporate input:
- Technical constraints → Adjust scope
- Design insights → Refine user flows
- Market feedback → Validate assumptions
**Expected Output:** Complete PRD with problem, solution, metrics, acceptance criteria, and stakeholder sign-off
**Time Estimate:** 1-2 weeks for comprehensive PRD (iterative process)
### Workflow 4: Quarterly Planning & OKR Setting
**Goal:** Plan quarterly product goals with prioritized initiatives and success metrics
**Steps:**
1. **Review Company OKRs** - Align product goals to business objectives:
- Review CEO/executive OKRs for quarter
- Identify product contribution areas
- Understand strategic priorities
2. **Run Feature Prioritization** - Use RICE for candidate features
```bash
python ../../product-team/product-manager-toolkit/scripts/rice_prioritizer.py q4-candidates.csv --capacity 18
```
3. **Define Product OKRs** - Set ambitious but achievable goals:
- **Objective**: Qualitative, inspirational (e.g., "Become the easiest platform to onboard")
- **Key Results**: Quantitative, measurable (e.g., "Reduce onboarding time from 30min to 10min")
- **Initiatives**: Features that drive key results
- **Metrics**: How we'll track progress weekly
4. **Capacity Planning** - Allocate team resources:
- Engineering capacity: Person-months available
- Design capacity: UI/UX support needed
- Buffer allocation: 20% for bugs, support, unknowns
- Dependency tracking: External blockers
5. **Risk Assessment** - Identify what could go wrong:
- Technical risks (scalability, performance)
- Market risks (competition, demand)
- Execution risks (dependencies, team velocity)
- Mitigation plans for each risk
6. **Stakeholder Review** - Present quarterly plan:
- OKRs with supporting initiatives
- RICE-justified priorities
- Resource allocation and capacity
- Risks and mitigation strategies
- Success metrics and tracking cadence
7. **Track Progress** - Weekly OKR check-ins:
- Update key result progress
- Adjust priorities if needed
- Communicate blockers early
**Expected Output:** Quarterly OKRs with prioritized roadmap, capacity plan, and risk mitigation
**Time Estimate:** 1 week for quarterly planning (last week of previous quarter)
## Integration Examples
### Example 1: Weekly Product Review Dashboard
```bash
#!/bin/bash
# product-weekly-review.sh - Automated product metrics summary
echo "📊 Weekly Product Review - $(date +%Y-%m-%d)"
echo "=========================================="
# Current roadmap status
echo ""
echo "🎯 Roadmap Priorities (RICE Sorted):"
python ../../product-team/product-manager-toolkit/scripts/rice_prioritizer.py current-roadmap.csv --capacity 20
# Recent interview insights
echo ""
echo "💡 Latest Customer Insights:"
if [ -f latest-interview.txt ]; then
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py latest-interview.txt
else
echo "No new interviews this week"
fi
# PRD templates available
echo ""
echo "📝 PRD Templates:"
echo "Standard PRD, One-Page PRD, Feature Brief, Agile Epic"
echo "Location: ../../product-team/product-manager-toolkit/references/prd_templates.md"
```
### Example 2: Discovery Sprint Workflow
```bash
# Complete discovery sprint (2 weeks)
echo "🔍 Discovery Sprint - Week 1"
echo "=============================="
# Day 1-2: Conduct interviews
echo "Conducting 5 customer interviews..."
# Day 3-5: Analyze insights
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-001.txt > insights-001.txt
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-002.txt > insights-002.txt
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-003.txt > insights-003.txt
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-004.txt > insights-004.txt
python ../../product-team/product-manager-toolkit/scripts/customer_interview_analyzer.py interview-005.txt > insights-005.txt
echo ""
echo "🔍 Discovery Sprint - Week 2"
echo "=============================="
# Day 6-8: Prioritize problems and solutions
echo "Creating solution candidates..."
# Day 9-10: RICE prioritization
python ../../product-team/product-manager-toolkit/scripts/rice_prioritizer.py solution-candidates.csv
echo ""
echo "✅ Discovery Complete - Ready for PRD creation"
```
### Example 3: Quarterly Planning Automation
```bash
# Quarterly planning automation script
QUARTER="Q4-2025"
CAPACITY=18 # person-months
echo "📅 $QUARTER Planning"
echo "===================="
# Step 1: Prioritize backlog
echo ""
echo "1. Feature Prioritization:"
python ../../product-team/product-manager-toolkit/scripts/rice_prioritizer.py backlog.csv --capacity $CAPACITY > $QUARTER-roadmap.txt
# Step 2: Extract quick wins
echo ""
echo "2. Quick Wins (Ship First):"
grep "Quick Win" $QUARTER-roadmap.txt
# Step 3: Identify big bets
echo ""
echo "3. Big Bets (Strategic Investments):"
grep "Big Bet" $QUARTER-roadmap.txt
# Step 4: Generate summary
echo ""
echo "4. Quarterly Summary:"
echo "Capacity: $CAPACITY person-months"
echo "Features: $(wc -l < backlog.csv)"
echo "Report: $QUARTER-roadmap.txt"
```
## Success Metrics
**Prioritization Effectiveness:**
- **Decision Speed:** <2 days from backlog review to roadmap commitment
- **Stakeholder Alignment:** >90% stakeholder agreement on priorities
- **RICE Validation:** 80%+ of shipped features match predicted impact
- **Portfolio Balance:** 40% quick wins, 40% big bets, 20% fill-ins
**Discovery Quality:**
- **Interview Volume:** 10-15 interviews per discovery sprint
- **Insight Extraction:** 5-10 high-priority pain points identified
- **Problem Validation:** 70%+ of prioritized problems validated before build
- **Time to Insight:** <1 week from interviews to prioritized problem list
**Requirements Quality:**
- **PRD Completeness:** 100% of PRDs include problem, solution, metrics, acceptance criteria
- **Stakeholder Review:** <3 days average PRD review cycle
- **Engineering Clarity:** >90% of PRDs require no clarification during development
- **Scope Accuracy:** >80% of features ship within original scope estimate
**Business Impact:**
- **Feature Adoption:** >60% of users adopt new features within 30 days
- **Problem Resolution:** >70% reduction in pain point severity post-launch
- **Revenue Impact:** Track revenue/retention lift from prioritized features
- **Development Efficiency:** 30%+ reduction in rework due to clear requirements
## Related Agents
- [cs-agile-product-owner](cs-agile-product-owner.md) - Sprint planning and user story generation (planned)
- [cs-product-strategist](cs-product-strategist.md) - OKR cascade and strategic planning (planned)
- [cs-ux-researcher](cs-ux-researcher.md) - Persona generation and user research (planned)
## References
- **Skill Documentation:** [../../product-team/product-manager-toolkit/SKILL.md](../../product-team/product-manager-toolkit/SKILL.md)
- **Product Domain Guide:** [../../product-team/CLAUDE.md](../../product-team/CLAUDE.md)
- **Agent Development Guide:** [../CLAUDE.md](../CLAUDE.md)
---
**Last Updated:** November 5, 2025
**Sprint:** sprint-11-05-2025 (Day 4)
**Status:** Production Ready
**Version:** 1.0

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---
name: cs-agent-name
description: One-line description of what this agent does (keep under 150 characters)
skills: skill-folder-name
domain: domain-name
model: sonnet
tools: [Read, Write, Bash, Grep, Glob]
---
# Agent Name
<!--
INSTRUCTIONS FOR USING THIS TEMPLATE:
1. Replace "cs-agent-name" with your agent's name (use kebab-case with cs- prefix)
2. Replace "Agent Name" with the display name (Title Case)
3. Fill in all sections below following the structure
4. Test all relative paths (../../) before committing
5. Ensure minimum 3 workflows documented
6. Provide concrete integration examples
7. Define measurable success metrics
EXAMPLES OF COMPLETED AGENTS:
- agents/marketing/cs-content-creator.md
- agents/marketing/cs-demand-gen-specialist.md
- agents/c-level/cs-ceo-advisor.md
- agents/c-level/cs-cto-advisor.md
- agents/product/cs-product-manager.md
-->
## Purpose
<!--
Write 2-3 paragraphs describing:
- What this agent does
- Who it's designed for (target users)
- How it enables better decisions/outcomes
- The specific gap it bridges
Example structure:
Paragraph 1: Agent's primary function and skill orchestration
Paragraph 2: Target audience and their pain points
Paragraph 3: Value proposition and outcome focus
-->
[Paragraph 1: Describe what this agent does and which skill package it orchestrates]
[Paragraph 2: Describe target users, their roles, and why they need this agent]
[Paragraph 3: Explain the gap this agent bridges and the outcomes it enables]
## Skill Integration
**Skill Location:** `../../domain-skill/skill-name/`
<!--
Document how this agent integrates with the underlying skill package.
Test all paths to ensure they resolve correctly from agents/domain/ directory.
-->
### Python Tools
<!--
List all Python automation tools from the skill package.
Minimum 1 tool, ideally 2-4 tools.
For each tool, provide:
- Clear purpose statement
- Exact file path (relative from agent location)
- Usage examples with arguments
- Key features
- Common use cases
-->
1. **Tool Name**
- **Purpose:** What this tool does (one sentence)
- **Path:** `../../domain-skill/skill-name/scripts/tool_name.py`
- **Usage:** `python ../../domain-skill/skill-name/scripts/tool_name.py [arguments]`
- **Features:** Key capabilities (bullet list)
- **Use Cases:** When to use this tool
2. **Second Tool** (if applicable)
- **Purpose:** What this tool does
- **Path:** `../../domain-skill/skill-name/scripts/second_tool.py`
- **Usage:** `python ../../domain-skill/skill-name/scripts/second_tool.py [arguments]`
- **Features:** Key capabilities
- **Use Cases:** When to use this tool
### Knowledge Bases
<!--
List reference documentation from the skill package.
These are markdown files with frameworks, best practices, templates.
-->
1. **Reference Name**
- **Location:** `../../domain-skill/skill-name/references/reference_file.md`
- **Content:** What knowledge this file contains
- **Use Case:** When to consult this reference
2. **Second Reference** (if applicable)
- **Location:** `../../domain-skill/skill-name/references/second_reference.md`
- **Content:** What knowledge this file contains
- **Use Case:** When to consult this reference
### Templates
<!--
List user-facing templates from the skill package's assets/ folder.
Optional section - only if skill has templates.
-->
1. **Template Name** (if applicable)
- **Location:** `../../domain-skill/skill-name/assets/template.md`
- **Use Case:** When users would copy and customize this template
## Workflows
<!--
Document MINIMUM 3 workflows. Ideally 4 workflows.
Each workflow must have: Goal, Steps, Expected Output, Time Estimate
Workflow types to consider:
- Primary use case (most common)
- Advanced use case (complex scenario)
- Integration use case (combining multiple tools)
- Automated workflow (scripting/batching)
-->
### Workflow 1: [Primary Use Case Name]
**Goal:** One-sentence description of what this workflow accomplishes
**Steps:**
1. **[Action Step]** - Description of first step
```bash
# Command example if applicable
python ../../domain-skill/skill-name/scripts/tool.py input.txt
```
2. **[Action Step]** - Description of second step
3. **[Action Step]** - Description of third step
4. **[Action Step]** - Description of fourth step
5. **[Action Step]** - Description of final step
**Expected Output:** What success looks like (deliverable, metric, decision made)
**Time Estimate:** How long this workflow typically takes
**Example:**
```bash
# Complete workflow example with real commands
command1
command2
# Review output
```
### Workflow 2: [Advanced Use Case Name]
**Goal:** One-sentence description
**Steps:**
1. **[Action Step]** - Description
2. **[Action Step]** - Description
3. **[Action Step]** - Description
4. **[Action Step]** - Description
**Expected Output:** What success looks like
**Time Estimate:** Duration estimate
### Workflow 3: [Integration Use Case Name]
**Goal:** One-sentence description
**Steps:**
1. **[Action Step]** - Description
2. **[Action Step]** - Description
3. **[Action Step]** - Description
**Expected Output:** What success looks like
**Time Estimate:** Duration estimate
### Workflow 4: [Optional Fourth Workflow]
<!-- Delete this section if you only have 3 workflows -->
**Goal:** One-sentence description
**Steps:**
1. **[Action Step]** - Description
2. **[Action Step]** - Description
**Expected Output:** What success looks like
**Time Estimate:** Duration estimate
## Integration Examples
<!--
Provide 2-3 concrete code examples showing real-world usage.
These should be copy-paste ready bash scripts or commands.
Example types:
- Weekly/daily automation scripts
- Multi-tool workflows
- Output processing examples
- Real-time monitoring
-->
### Example 1: [Example Name]
```bash
#!/bin/bash
# script-name.sh - Brief description
# Setup variables
INPUT_FILE=$1
# Execute workflow
python ../../domain-skill/skill-name/scripts/tool.py "$INPUT_FILE"
# Process output
echo "Analysis complete. Review results above."
```
### Example 2: [Example Name]
```bash
# Multi-step workflow example
# Step 1: Prepare data
echo "Step 1: Data preparation"
# Step 2: Run analysis
python ../../domain-skill/skill-name/scripts/tool.py input.csv
# Step 3: Generate report
echo "Report generation complete"
```
### Example 3: [Example Name]
```bash
# Automation example (e.g., weekly report, daily check)
DATE=$(date +%Y-%m-%d)
echo "📊 Report for $DATE"
# Execute tools
python ../../domain-skill/skill-name/scripts/tool.py current-data.csv > report-$DATE.txt
```
## Success Metrics
<!--
Define how to measure this agent's effectiveness.
Group metrics into logical categories (3-4 categories).
Each metric should be specific and measurable.
Categories might include:
- Quality metrics
- Efficiency metrics
- Business impact metrics
- User satisfaction metrics
-->
**[Metric Category 1]:**
- **[Metric Name]:** Target value or improvement percentage
- **[Metric Name]:** Target value or improvement percentage
- **[Metric Name]:** Target value or improvement percentage
**[Metric Category 2]:**
- **[Metric Name]:** Target value or improvement percentage
- **[Metric Name]:** Target value or improvement percentage
**[Metric Category 3]:**
- **[Metric Name]:** Target value or improvement percentage
- **[Metric Name]:** Target value or improvement percentage
**[Metric Category 4]** (optional):
- **[Metric Name]:** Target value or improvement percentage
## Related Agents
<!--
Cross-reference other agents in the same domain or related domains.
Use relative paths from agents/ directory.
Explain how agents complement each other.
-->
- [cs-related-agent](../domain/cs-related-agent.md) - How this agent relates (e.g., "Provides strategic context for tactical execution")
- [cs-another-agent](cs-another-agent.md) - How this agent relates (same directory)
- [cs-future-agent](cs-future-agent.md) - Planned agent (mark as "planned")
## References
<!--
Link to all related documentation.
Always include these three links with correct relative paths.
-->
- **Skill Documentation:** [../../domain-skill/skill-name/SKILL.md](../../domain-skill/skill-name/SKILL.md)
- **Domain Guide:** [../../domain-skill/CLAUDE.md](../../domain-skill/CLAUDE.md)
- **Agent Development Guide:** [../CLAUDE.md](../CLAUDE.md)
---
<!--
Update metadata when publishing.
Sprint format: sprint-MM-DD-YYYY
Status: Production Ready, Beta, Alpha
-->
**Last Updated:** [Date]
**Sprint:** [sprint-MM-DD-YYYY] (Day X)
**Status:** Production Ready
**Version:** 1.0