
User Research
- 22 installs
- 3 repo stars
- Updated January 5, 2026
- pluginagentmarketplace/custom-plugin-product-manager
Helps with ai & agent building tasks.
About
user-research is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.
- user-research
- AI & Agent Building
- AI-coding skill
User Research by the numbers
- 22 all-time installs (skills.sh)
- Ranked #10,137 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/pluginagentmarketplace/custom-plugin-product-manager --skill user-researchAdd your badge
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| Installs | 22 |
|---|---|
| repo stars | ★ 3 |
| Last updated | January 5, 2026 |
| Repository | pluginagentmarketplace/custom-plugin-product-manager ↗ |
What it does
Helps with ai & agent building tasks.
Files
User Research Skill
Conduct effective user research to understand customer needs, behaviors, and pain points. Master interview techniques and insight synthesis.
Research Methods
Method Selection Guide
| Method | When | Sample | Duration |
|---|---|---|---|
| Interviews | Deep understanding | 15-25 | 45-60 min |
| Surveys | Quantitative validation | 100+ | 5-10 min |
| Usability | UX issues | 5-8 | 30-60 min |
| Observation | Real behavior | 3-5 | 2-4 hours |
| Analytics | Scale patterns | All users | Ongoing |
Qualitative Research
Interview Structure
OPENING (5 min):
- Intro & rapport
- Permission to record
- Context setting
CONTEXT (10 min):
- Role and responsibilities
- Day-to-day workflow
- Tools used
DEEP DIVE (20 min):
- "Walk me through [process]..."
- "Tell me about last time [problem]..."
- "What frustrates you most?"
IMPACT (10 min):
- "What happens when [problem]?"
- "How much time/money does it cost?"
FUTURE (10 min):
- "What would ideal look like?"
- "What would you pay for [solution]?"
CLOSING (5 min):
- "Anything else?"
- "Can I follow up?"Interview Best Practices
- Listen 70%, talk 30%
- Ask "Why?" 5 times
- Avoid leading questions
- Use silence effectively
- Capture quotes verbatim
Quantitative Research
Survey Design
Question Types:
- Rating scale (1-5, 1-10)
- Multiple choice
- Open-ended (limit 1-2)
- Ranking
NPS Question: "How likely are you to recommend [product] to a friend? (0-10)"
Sample Size Calculator
For 95% confidence, 5% margin:
- Population 100 → Sample 80
- Population 500 → Sample 217
- Population 1000 → Sample 278
- Population 10000 → Sample 370Synthesis
Affinity Mapping
1. Write each insight on sticky note 2. Group similar insights 3. Name each group (theme) 4. Rank by frequency/impact 5. Extract top 5-10 themes
Persona Template
NAME: [Descriptive name]
ROLE: [Job title, company type]
QUOTE: "[Real quote from research]"
GOALS:
- [Goal 1]
- [Goal 2]
FRUSTRATIONS:
- [Pain 1]
- [Pain 2]
BEHAVIORS:
- [How they work]
- [Tools they use]
NEEDS:
- [Need 1]
- [Need 2]Journey Map
| Stage | Actions | Emotions | Pain Points | Opportunities |
|---|---|---|---|---|
| Aware | Search | Curious | Hard to find | SEO, content |
| Consider | Compare | Confused | Too many options | Comparison |
| Purchase | Buy | Anxious | Complex checkout | Simplify |
| Use | Onboard | Overwhelmed | Steep learning | Better UX |
Troubleshooting
Yaygın Hatalar & Çözümler
| Hata | Olası Sebep | Çözüm |
|---|---|---|
| Low response | Wrong incentive | $50-100 gift card |
| Surface insights | Leading questions | "Why?" 5x |
| Conflicting data | Mixed segments | Segment analysis |
| No show | Scheduling issues | Calendar hold, reminder |
Debug Checklist
[ ] Research plan documented mi?
[ ] Sample size sufficient mi?
[ ] Questions non-leading mi?
[ ] Recording consent alındı mı?
[ ] Synthesis done within 24h mi?
[ ] Insights actionable mi?Recovery Procedures
1. Low Participation → Increase incentive, new channels 2. Conflicting Data → Segment by user type 3. Shallow Insights → Follow-up interviews
Learning Outcomes
- Plan effective research studies
- Conduct insightful interviews
- Design valid surveys
- Synthesize research data
- Present actionable insights
# user-research Configuration
# Category: general
# Generated: 2025-12-30
skill:
name: user-research
version: "1.0.0"
category: general
settings:
# Default settings for user-research
enabled: true
log_level: info
# Category-specific defaults
validation:
strict_mode: false
auto_fix: false
output:
format: markdown
include_examples: true
# Environment-specific overrides
environments:
development:
log_level: debug
validation:
strict_mode: false
production:
log_level: warn
validation:
strict_mode: true
# Integration settings
integrations:
# Enable/disable integrations
git: true
linter: true
formatter: true
{
"$schema": "http://json-schema.org/draft-07/schema#",
"title": "user-research Configuration Schema",
"type": "object",
"properties": {
"skill": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"version": {
"type": "string",
"pattern": "^\\d+\\.\\d+\\.\\d+$"
},
"category": {
"type": "string",
"enum": [
"api",
"testing",
"devops",
"security",
"database",
"frontend",
"algorithms",
"machine-learning",
"cloud",
"containers",
"general"
]
}
},
"required": [
"name",
"version"
]
},
"settings": {
"type": "object",
"properties": {
"enabled": {
"type": "boolean",
"default": true
},
"log_level": {
"type": "string",
"enum": [
"debug",
"info",
"warn",
"error"
]
}
}
}
},
"required": [
"skill"
]
}User Research Guide
Overview
This guide provides comprehensive documentation for the user-research skill in the custom-plugin-product-manager plugin.
Category: General
Quick Start
Prerequisites
- Familiarity with general concepts
- Development environment set up
- Plugin installed and configured
Basic Usage
# Invoke the skill
claude "user-research - [your task description]"
# Example
claude "user-research - analyze the current implementation"Core Concepts
Key Principles
1. Consistency - Follow established patterns 2. Clarity - Write readable, maintainable code 3. Quality - Validate before deployment
Best Practices
- Always validate input data
- Handle edge cases explicitly
- Document your decisions
- Write tests for critical paths
Common Tasks
Task 1: Basic Implementation
# Example implementation pattern
def implement_user_research(input_data):
"""
Implement user-research functionality.
Args:
input_data: Input to process
Returns:
Processed result
"""
# Validate input
if not input_data:
raise ValueError("Input required")
# Process
result = process(input_data)
# Return
return resultTask 2: Advanced Usage
For advanced scenarios, consider:
- Configuration customization via
assets/config.yaml - Validation using
scripts/validate.py - Integration with other skills
Troubleshooting
Common Issues
| Issue | Cause | Solution |
|---|---|---|
| Skill not found | Not installed | Run plugin sync |
| Validation fails | Invalid config | Check config.yaml |
| Unexpected output | Missing context | Provide more details |
Related Resources
- SKILL.md - Skill specification
- config.yaml - Configuration options
- validate.py - Validation script
---
Last updated: 2025-12-30
User Research Patterns
Design Patterns
Pattern 1: Input Validation
Always validate input before processing:
def validate_input(data):
if data is None:
raise ValueError("Data cannot be None")
if not isinstance(data, dict):
raise TypeError("Data must be a dictionary")
return TruePattern 2: Error Handling
Use consistent error handling:
try:
result = risky_operation()
except SpecificError as e:
logger.error(f"Operation failed: {e}")
handle_error(e)
except Exception as e:
logger.exception("Unexpected error")
raisePattern 3: Configuration Loading
Load and validate configuration:
import yaml
def load_config(config_path):
with open(config_path) as f:
config = yaml.safe_load(f)
validate_config(config)
return configAnti-Patterns to Avoid
❌ Don't: Swallow Exceptions
# BAD
try:
do_something()
except:
pass✅ Do: Handle Explicitly
# GOOD
try:
do_something()
except SpecificError as e:
logger.warning(f"Expected error: {e}")
return default_valueCategory-Specific Patterns: General
Recommended Approach
1. Start with the simplest implementation 2. Add complexity only when needed 3. Test each addition 4. Document decisions
Common Integration Points
- Configuration:
assets/config.yaml - Validation:
scripts/validate.py - Documentation:
references/GUIDE.md
---
Pattern library for user-research skill
#!/usr/bin/env python3
"""
Validation script for user-research skill.
Category: general
"""
import os
import sys
import yaml
import json
from pathlib import Path
def validate_config(config_path: str) -> dict:
"""
Validate skill configuration file.
Args:
config_path: Path to config.yaml
Returns:
dict: Validation result with 'valid' and 'errors' keys
"""
errors = []
if not os.path.exists(config_path):
return {"valid": False, "errors": ["Config file not found"]}
try:
with open(config_path, 'r') as f:
config = yaml.safe_load(f)
except yaml.YAMLError as e:
return {"valid": False, "errors": [f"YAML parse error: {e}"]}
# Validate required fields
if 'skill' not in config:
errors.append("Missing 'skill' section")
else:
if 'name' not in config['skill']:
errors.append("Missing skill.name")
if 'version' not in config['skill']:
errors.append("Missing skill.version")
# Validate settings
if 'settings' in config:
settings = config['settings']
if 'log_level' in settings:
valid_levels = ['debug', 'info', 'warn', 'error']
if settings['log_level'] not in valid_levels:
errors.append(f"Invalid log_level: {settings['log_level']}")
return {
"valid": len(errors) == 0,
"errors": errors,
"config": config if not errors else None
}
def validate_skill_structure(skill_path: str) -> dict:
"""
Validate skill directory structure.
Args:
skill_path: Path to skill directory
Returns:
dict: Structure validation result
"""
required_dirs = ['assets', 'scripts', 'references']
required_files = ['SKILL.md']
errors = []
# Check required files
for file in required_files:
if not os.path.exists(os.path.join(skill_path, file)):
errors.append(f"Missing required file: {file}")
# Check required directories
for dir in required_dirs:
dir_path = os.path.join(skill_path, dir)
if not os.path.isdir(dir_path):
errors.append(f"Missing required directory: {dir}/")
else:
# Check for real content (not just .gitkeep)
files = [f for f in os.listdir(dir_path) if f != '.gitkeep']
if not files:
errors.append(f"Directory {dir}/ has no real content")
return {
"valid": len(errors) == 0,
"errors": errors,
"skill_name": os.path.basename(skill_path)
}
def main():
"""Main validation entry point."""
skill_path = Path(__file__).parent.parent
print(f"Validating user-research skill...")
print(f"Path: {skill_path}")
# Validate structure
structure_result = validate_skill_structure(str(skill_path))
print(f"\nStructure validation: {'PASS' if structure_result['valid'] else 'FAIL'}")
if structure_result['errors']:
for error in structure_result['errors']:
print(f" - {error}")
# Validate config
config_path = skill_path / 'assets' / 'config.yaml'
if config_path.exists():
config_result = validate_config(str(config_path))
print(f"\nConfig validation: {'PASS' if config_result['valid'] else 'FAIL'}")
if config_result['errors']:
for error in config_result['errors']:
print(f" - {error}")
else:
print("\nConfig validation: SKIPPED (no config.yaml)")
# Summary
all_valid = structure_result['valid']
print(f"\n==================================================")
print(f"Overall: {'VALID' if all_valid else 'INVALID'}")
return 0 if all_valid else 1
if __name__ == "__main__":
sys.exit(main())