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# Agent Prompts for LinkedIn Profile Enhancer
class ContentPrompts:
"""Collection of prompts for content generation agents"""
def __init__(self):
self.headline_prompts = HeadlinePrompts()
self.about_prompts = AboutPrompts()
self.experience_prompts = ExperiencePrompts()
self.general_prompts = GeneralPrompts()
class HeadlinePrompts:
"""Prompts for headline optimization"""
HEADLINE_ANALYSIS = """
Analyze this LinkedIn headline and provide improvement suggestions:
Current headline: "{headline}"
Target role: "{target_role}"
Key skills: {skills}
Consider:
1. Keyword optimization for the target role
2. Value proposition clarity
3. Professional branding
4. Character limit (120 chars max)
5. Industry-specific terms
Provide 3-5 alternative headline suggestions.
"""
HEADLINE_TEMPLATES = [
"{title} | {specialization} | {key_skills}",
"{seniority} {title} specializing in {domain} | {achievement}",
"{title} | Helping {target_audience} with {solution} | {technologies}",
"{role} with {years}+ years in {industry} | {unique_value_prop}"
]
class AboutPrompts:
"""Prompts for about section optimization"""
ABOUT_STRUCTURE = """
Create an engaging LinkedIn About section with this structure:
Profile info:
- Name: {name}
- Current role: {current_role}
- Years of experience: {experience_years}
- Key skills: {key_skills}
- Notable achievements: {achievements}
- Target audience: {target_audience}
Structure:
1. Hook (compelling opening line)
2. Professional summary (2-3 sentences)
3. Key expertise and skills
4. Notable achievements with metrics
5. Call to action
Keep it conversational, professional, and under 2000 characters.
"""
ABOUT_HOOKS = [
"π Passionate about transforming {industry} through {technology}",
"π‘ {Years} years of turning complex {domain} challenges into simple solutions",
"π― Helping {target_audience} achieve {outcome} through {approach}",
"β‘ {Achievement} specialist with a track record of {impact}"
]
class ExperiencePrompts:
"""Prompts for experience section optimization"""
EXPERIENCE_ENHANCEMENT = """
Enhance this work experience entry:
Current description: "{description}"
Role: {title}
Company: {company}
Duration: {duration}
Improve by:
1. Starting with strong action verbs
2. Adding quantified achievements
3. Highlighting relevant skills used
4. Showing business impact
5. Using bullet points for readability
Target the experience for: {target_role}
"""
ACTION_VERBS = {
"Leadership": ["led", "managed", "directed", "coordinated", "supervised"],
"Achievement": ["achieved", "delivered", "exceeded", "accomplished", "attained"],
"Development": ["developed", "created", "built", "designed", "implemented"],
"Improvement": ["optimized", "enhanced", "streamlined", "upgraded", "modernized"],
"Problem-solving": ["resolved", "troubleshot", "analyzed", "diagnosed", "solved"]
}
class GeneralPrompts:
"""General prompts for profile enhancement"""
SKILLS_OPTIMIZATION = """
Optimize this skills list for the target role:
Current skills: {current_skills}
Target role: {target_role}
Job description keywords: {job_keywords}
Provide:
1. Priority ranking of current skills
2. Missing skills to add
3. Skills to remove or deprioritize
4. Skill categories organization
"""
KEYWORD_OPTIMIZATION = """
Analyze keyword optimization for this profile:
Profile content: {profile_content}
Target job description: {job_description}
Identify:
1. Current keyword density
2. Missing important keywords
3. Over-optimized keywords
4. Natural integration suggestions
5. Industry-specific terminology gaps
"""
PROFILE_AUDIT = """
Conduct a comprehensive LinkedIn profile audit:
Profile data: {profile_data}
Target role: {target_role}
Industry: {industry}
Audit areas:
1. Profile completeness (%)
2. Keyword optimization
3. Content quality and engagement potential
4. Professional branding consistency
5. Call-to-action effectiveness
6. Visual elements (photo, banner) recommendations
Provide actionable improvement suggestions with priority levels.
"""
class AnalysisPrompts:
"""Prompts for profile analysis"""
COMPETITIVE_ANALYSIS = """
Compare this profile against industry standards:
Profile: {profile_data}
Industry: {industry}
Seniority level: {seniority}
Analyze:
1. Profile completeness vs industry average
2. Keyword usage vs competitors
3. Content quality benchmarks
4. Engagement potential indicators
5. Areas of competitive advantage
6. Improvement opportunities
"""
CONTENT_QUALITY = """
Assess content quality across this LinkedIn profile:
Profile sections: {profile_sections}
Evaluate:
1. Clarity and readability
2. Professional tone consistency
3. Value proposition strength
4. Quantified achievements presence
5. Industry relevance
6. Call-to-action effectiveness
Rate each section 1-10 and provide specific improvement suggestions.
"""
class JobMatchingPrompts:
"""Prompts for job matching analysis"""
JOB_MATCH_ANALYSIS = """
Analyze how well this profile matches the job requirements:
Profile: {profile_data}
Job description: {job_description}
Match analysis:
1. Skills alignment (%)
2. Experience relevance
3. Keyword overlap
4. Education/certification fit
5. Overall match score
Provide specific recommendations to improve match score.
"""
TAILORING_SUGGESTIONS = """
Suggest profile modifications to better match this opportunity:
Current profile: {profile_data}
Target job: {job_description}
Match score: {current_match_score}
Prioritized suggestions:
1. High-impact changes (immediate wins)
2. Medium-impact improvements
3. Long-term development areas
4. Skills to highlight/add
5. Content restructuring recommendations
"""
# Utility functions for prompt formatting
def format_prompt(template: str, **kwargs) -> str:
"""Format prompt template with provided variables"""
try:
return template.format(**kwargs)
except KeyError as e:
return f"Error formatting prompt: Missing variable {e}"
def get_prompt_by_category(category: str, prompt_name: str) -> str:
"""Get a specific prompt by category and name"""
prompt_classes = {
'headline': HeadlinePrompts(),
'about': AboutPrompts(),
'experience': ExperiencePrompts(),
'general': GeneralPrompts(),
'analysis': AnalysisPrompts(),
'job_matching': JobMatchingPrompts()
}
prompt_class = prompt_classes.get(category.lower())
if not prompt_class:
return f"Category '{category}' not found"
prompt = getattr(prompt_class, prompt_name.upper(), None)
if not prompt:
return f"Prompt '{prompt_name}' not found in category '{category}'"
return prompt
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