email-formatter

Transform rough email drafts into polished, professional messages. Use this skill when the user wants to improve email quality, fix grammar and tone, format business emails, or convert casual messages into professional communication. Triggers include: 'format my email', 'make this professional', 'improve this message', 'fix my email', 'polish this draft', or any request to enhance email writing quality. Also use when converting bullet points or notes into complete emails, adjusting tone (formal/casual/friendly), or preparing important messages for clients, managers, or stakeholders.

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Repositório: johnalbertini14-glitch/openclaw-skills
Última atividade na origem: 12 de fevereiro de 2026 às 07:36
Idioma detectado do SKILL.md: inglês
Estrelas: 1
Forks: 0

Opções de instalação

Por padrão, está selecionado o prompt que primeiro revisa a origem. Você pode mudar para um comando direto ou baixar uma cópia local.

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

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npx skills add https://github.com/johnalbertini14-glitch/openclaw-skills --skill email-formatter

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vincent-polymarket-for-agents

Use this skill to create a Polymarket wallet for your agent and trade on prediction markets. Browse markets, place bets, manage positions — all without exposing private keys.

2026-02-25

clawsec-suite

ClawSec suite manager with embedded advisory-feed monitoring, cryptographic signature verification, approval-gated malicious-skill response, and guided setup for additional security skills.

2026-02-25

openclaw-audit-watchdog

Automated daily security audits for OpenClaw agents with email reporting. Runs deep audits and sends formatted reports.

2026-02-25

Ver todas deste repositório

#!/usr/bin/env python3 """ Analyze email tone Usage: python3 tone_analyzer.py "email text" """ import sys import re def analyze_tone(text): """Detect tone indicators in email text""" # Formal indicators formal_words = ['pursuant', 'hereby', 'aforementioned', 'regarding', 'sincerely', 'respectfully', 'cordially'] # Casual indicators casual_words = ['hey', 'gonna', 'wanna', 'yeah', 'yep', 'nope', 'btw', 'fyi', 'lol', 'omg', 'tbh'] # Aggressive indicators aggressive_words = ['immediately', 'must', 'unacceptable', 'ridiculous', 'obviously', 'clearly', 'need to', 'have to'] # Polite indicators polite_words = ['please', 'kindly', 'would you', 'could you', 'appreciate', 'thank', 'grateful'] text_lower = text.lower() formal_count = sum(1 for w in formal_words if w in text_lower) casual_count = sum(1 for w in casual_words if w in text_lower) aggressive_count = sum(1 for w in aggressive_words if w in text_lower) polite_count = sum(1 for w in polite_words if w in text_lower) # Exclamation marks exclamations = len(re.findall(r'!', text)) # ALL CAPS detection caps_words = len(re.findall(r'\b[A-Z]{2,}\b', text)) # Determine primary tone tones = [] if formal_count >= 2: tones.append("FORMAL") if casual_count >= 2: tones.append("CASUAL") if aggressive_count >= 2 or caps_words >= 2: tones.append("AGGRESSIVE") if polite_count >= 2: tones.append("POLITE") if exclamations >= 3: tones.append("ENTHUSIASTIC/URGENT") if not tones: tones.append("NEUTRAL") return { 'primary_tone': tones[0], 'all_tones': tones, 'formal_score': formal_count, 'casual_score': casual_count, 'aggressive_score': aggressive_count, 'polite_score': polite_count, 'exclamations': exclamations, 'caps_words': caps_words } if __name__ == "__main__": if len(sys.argv) < 2: print("Usage: python3 tone_analyzer.py 'text'") sys.exit(1) result = analyze_tone(sys.argv[1]) print(f"📊 Primary Tone: {result['primary_tone']}") print(f"🎯 All Tones: {', '.join(result['all_tones'])}") print(f"📈 Scores - Formal:{result['formal_score']} Casual:{result['casual_score']} " f"Aggressive:{result['aggressive_score']} Polite:{result['polite_score']}") if result['aggressive_score'] >= 2: print("⚠️ WARNING: Email may sound aggressive") if result['exclamations'] >= 3: print("⚠️ WARNING: Too many exclamation marks") if result['caps_words'] >= 2: print("⚠️ WARNING: Excessive capitalization detected")

#!/usr/bin/env python3 """ Calculate email readability Usage: python3 readability.py "email text" """ import sys import re def count_syllables(word): """Simple syllable counter""" word = word.lower() vowels = 'aeiouy' syllable_count = 0 previous_was_vowel = False for char in word: is_vowel = char in vowels if is_vowel and not previous_was_vowel: syllable_count += 1 previous_was_vowel = is_vowel # Adjust for silent 'e' if word.endswith('e'): syllable_count -= 1 # Every word has at least one syllable if syllable_count == 0: syllable_count = 1 return syllable_count def flesch_reading_ease(text): """Calculate Flesch Reading Ease score""" sentences = len(re.findall(r'[.!?]+', text)) or 1 words = len(text.split()) syllables = sum(count_syllables(word) for word in text.split()) if words == 0: return 0 score = 206.835 - 1.015 * (words / sentences) - 84.6 * (syllables / words) return round(score, 1) def analyze_readability(text): """Analyze email readability""" words = text.split() sentences = len(re.findall(r'[.!?]+', text)) or 1 avg_word_length = sum(len(w) for w in words) / len(words) if words else 0 avg_sentence_length = len(words) / sentences flesch_score = flesch_reading_ease(text) # Interpret score if flesch_score >= 90: level = "Very Easy (5th grade)" elif flesch_score >= 80: level = "Easy (6th grade)" elif flesch_score >= 70: level = "Fairly Easy (7th grade)" elif flesch_score >= 60: level = "Standard (8-9th grade)" elif flesch_score >= 50: level = "Fairly Difficult (10-12th grade)" elif flesch_score >= 30: level = "Difficult (College)" else: level = "Very Difficult (Graduate)" return { 'flesch_score': flesch_score, 'level': level, 'avg_word_length': round(avg_word_length, 1), 'avg_sentence_length': round(avg_sentence_length, 1), 'total_words': len(words), 'total_sentences': sentences } if __name__ == "__main__": if len(sys.argv) < 2: print("Usage: python3 readability.py 'text'") sys.exit(1) result = analyze_readability(sys.argv[1]) print(f"📖 Flesch Reading Ease: {result['flesch_score']}") print(f"📚 Reading Level: {result['level']}") print(f"📊 Stats: {result['total_words']} words, {result['total_sentences']} sentences") print(f"📏 Avg: {result['avg_word_length']} chars/word, {result['avg_sentence_length']} words/sentence") # Recommendations if result['flesch_score'] < 60: print("💡 TIP: Simplify language for better clarity") if result['avg_sentence_length'] > 20: print("💡 TIP: Break long sentences into shorter ones")

#!/usr/bin/env python3 """ ULTRA-SECURE Email Scanner - Multi-Layer Threat Detection Usage: python3 security_scan.py "email text" Exit codes: 0=safe, 1=warning, 2=critical_block, 3=report_required """ import sys import re import json from datetime import datetime class SecurityScanner: """Military-grade email security scanner""" def __init__(self): self.threat_level = 0 # 0=safe, 1=warning, 2=critical, 3=report self.violations = [] self.warnings = [] def scan(self, text): """Run all security checks""" # Layer 1: Zero Tolerance Patterns self.check_zero_tolerance(text) # Layer 2: Financial Fraud self.check_financial_fraud(text) # Layer 3: Impersonation self.check_impersonation(text) # Layer 4: Credential Harvesting self.check_credential_harvesting(text) # Layer 5: Threats & Violence self.check_threats(text) # Layer 6: Harassment & Discrimination self.check_harassment(text) # Layer 7: Privacy & PII self.check_privacy_violations(text) # Layer 8: Social Engineering self.check_social_engineering(text) # Layer 9: Child Safety self.check_child_safety(text) # Layer 10: Malicious Patterns self.check_malicious_patterns(text) return self.generate_report() def check_zero_tolerance(self, text): """Critical patterns that immediately block""" text_lower = text.lower() critical_patterns = [ # Credentials (r'(send|give|provide|email).{0,30}(password|pwd|credential|login|passphrase)', 'CREDENTIAL_REQUEST', 3), (r'verify.{0,20}(password|account|identity|credential)', 'FAKE_VERIFICATION', 3), (r'(username|user id).{0,20}(and|&|\\+).{0,20}password', 'CREDENTIAL_PAIR_REQUEST', 3), # Financial (r'wire transfer.{0,30}(urgent|immediate|asap|now|today)', 'URGENT_WIRE_TRANSFER', 3), (r'(gift card|itunes|steam|amazon card).{0,30}(buy|purchase|get|send)', 'GIFT_CARD_SCAM', 3), (r'(bitcoin|btc|crypto|ethereum|eth).{0,30}(wallet|address|send|transfer)', 'CRYPTO_SCAM', 3), (r'(bank account|routing number|swift code).{0,30}(provide|send|give)', 'BANKING_INFO_REQUEST', 3), # Impersonation (r"i'?m.{0,10}(from|with|calling from).{0,30}(IT|support|tech|help desk)", 'IT_IMPERSONATION', 3), (r"(this is|i am|i'm).{0,20}(CEO|CFO|president|director|executive)", 'EXECUTIVE_IMPERSONATION', 3), (r"(IRS|FBI|police|government|immigration).{0,30}(contact|reach out|notice)", 'AUTHORITY_IMPERSONATION', 3), # Threats (r'(or else|otherwise).{0,30}(fire|terminate|sue|report|arrest)', 'THREAT_DETECTED', 3), (r"(you|i)'?(ll| will).{0,30}(regret|pay|suffer|sorry)", 'THREAT_LANGUAGE', 3), # Child Safety (r'(child|minor|kid|teen|underage).{0,50}(meet|date|relationship|romantic)', 'CHILD_SAFETY_VIOLATION', 3), # Malware (r'(click|open|download).{0,20}(attachment|link|file).{0,20}(urgent|expire|suspend)', 'PHISHING_LINK', 3), ] for pattern, violation_type, severity in critical_patterns: if re.search(pattern, text_lower): self.add_violation(violation_type, severity, pattern) def check_financial_fraud(self, text): """Detect financial scam patterns""" text_lower = text.lower() fraud_indicators = [ (r'(won|winner|prize|lottery).{0,30}(\$|dollar|money|claim)', 'LOTTERY_SCAM', 2), (r'(inheritance|beneficiary|estate).{0,50}(million|claim|transfer)', 'INHERITANCE_SCAM', 2), (r'(tax|irs).{0,30}(refund|owe|pay immediately)', 'TAX_SCAM', 2), (r'(invoice|payment).{0,20}(overdue|urgent|immediate|final notice)', 'FAKE_INVOICE', 2), (r'(suspended|frozen|locked).{0,30}account', 'ACCOUNT_SUSPENSION_SCAM', 2), (r'(refund|reimbursement).{0,30}(click|verify|confirm)', 'REFUND_SCAM', 2), (r'(investment|opportunity|profit).{0,50}(guaranteed|risk-free|double)', 'INVESTMENT_FRAUD', 2), ] for pattern, violation_type, severity in fraud_indicators: if re.search(pattern, text_lower): self.add_violation(violation_type, severity, pattern) def check_impersonation(self, text): """Detect impersonation attempts""" text_lower = text.lower() impersonation_patterns = [ (r'(on behalf of|representing).{0,30}(company|organization|government)', 'UNAUTHORIZED_REPRESENTATION', 2), (r"(i'?m|this is).{0,20}(calling|writing|reaching out).{0,20}(from|regarding)", 'SUSPICIOUS_INTRODUCTION', 1), (r'(verify|confirm).{0,20}(you are|your identity|who you are)', 'IDENTITY_VERIFICATION_REQUEST', 2), ] for pattern, violation_type, severity in impersonation_patterns: if re.search(pattern, text_lower): self.add_violation(violation_type, severity, pattern) def check_credential_harvesting(self, text): """Detect credential theft attempts""" text_lower = text.lower() patterns = [ (r'(account|access).{0,30}(expire|suspend|lock|disable)', 'FAKE_EXPIRATION', 2), (r'(security|unusual|suspicious).{0,30}activity', 'FAKE_SECURITY_ALERT', 2), (r'(update|verify|confirm).{0,30}(payment|billing) (method|information)', 'PAYMENT_INFO_PHISHING', 2), (r'(reset|recover|change).{0,20}password.{0,20}(click|link|here)', 'PASSWORD_RESET_SCAM', 2), ] for pattern, violation_type, severity in patterns: if re.search(pattern, text_lower): self.add_violation(violation_type, severity, pattern) def check_threats(self, text): """Detect threats and violent language""" text_lower = text.lower() threat_words = [ 'kill', 'hurt', 'harm', 'destroy', 'eliminate', 'punish', 'revenge', 'retaliate', 'get back at', 'make you pay' ] for word in threat_words: if word in text_lower: self.add_violation('THREAT_LANGUAGE', 3, f"Threat word: {word}") # Physical threat patterns if re.search(r'(come after|find you|know where you)', text_lower): self.add_violation('PHYSICAL_THREAT', 3, 'Physical threat implied') def check_harassment(self, text): """Detect harassment and hostile language""" text_lower = text.lower() hostile_words = [ 'stupid', 'idiot', 'moron', 'incompetent', 'worthless', 'pathetic', 'useless', 'loser', 'failure', 'trash' ] count = sum(1 for word in hostile_words if word in text_lower) if count >= 2: self.add_violation('HARASSMENT', 2, f'{count} hostile terms detected') elif count == 1: self.add_warning('POTENTIALLY_HOSTILE', 'Hostile language detected') # Discriminatory patterns protected_characteristics = [ (r'(because|since).{0,20}(you\'?re|you are).{0,20}(woman|female|girl)', 'GENDER_DISCRIMINATION'), (r'(because|since).{0,20}(you\'?re|you are).{0,20}(old|young|age)', 'AGE_DISCRIMINATION'), (r'(people like you|your kind|you people)', 'DISCRIMINATORY_LANGUAGE'), ] for pattern, violation_type in protected_characteristics: if re.search(pattern, text_lower): self.add_violation(violation_type, 3, pattern) def check_privacy_violations(self, text): """Detect PII and privacy issues""" # SSN pattern if re.search(r'\b\d{3}-\d{2}-\d{4}\b', text): self.add_violation('SSN_DETECTED', 2, 'Social Security Number found') # Credit card pattern if re.search(r'\b\d{4}[\s-]?\d{4}[\s-]?\d{4}[\s-]?\d{4}\b', text): self.add_violation('CREDIT_CARD_DETECTED', 2, 'Credit card number found') # Email addresses (multiple) emails = re.findall(r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b', text) if len(emails) > 3: self.add_warning('MULTIPLE_EMAILS', f'{len(emails)} email addresses found') # Phone numbers (multiple) phones = re.findall(r'\b\d{3}[-.]?\d{3}[-.]?\d{4}\b', text) if len(phones) > 2: self.add_warning('MULTIPLE_PHONES', f'{len(phones)} phone numbers found') # Home address pattern if re.search(r'\d+\s+\w+\s+(street|st|avenue|ave|road|rd|drive|dr)', text.lower()): self.add_warning('ADDRESS_DETECTED', 'Physical address found') def check_social_engineering(self, text): """Detect social engineering tactics""" text_lower = text.lower() # Urgency indicators urgency_words = ['urgent', 'immediate', 'asap', 'right now', 'immediately', 'emergency', 'critical', 'time-sensitive'] urgency_count = sum(1 for word in urgency_words if word in text_lower) if urgency_count >= 3: self.add_violation('ARTIFICIAL_URGENCY', 2, f'{urgency_count} urgency indicators') elif urgency_count >= 2: self.add_warning('URGENCY_DETECTED', 'Multiple urgency indicators') # Secrecy requests if re.search(r"(don't tell|keep (this )?secret|confidential|between us)", text_lower): self.add_violation('SECRECY_REQUEST', 2, 'Requesting secrecy') # Authority bypass if re.search(r'(bypass|skip|ignore).{0,20}(normal|usual|standard) (process|procedure)', text_lower): self.add_violation('PROCESS_BYPASS', 2, 'Attempting to bypass normal procedures') # Too good to be true if re.search(r'(free|win|won|winner|selected|chosen).{0,30}(prize|money|gift|\$)', text_lower): self.add_warning('TOO_GOOD_TO_BE_TRUE', 'Unrealistic offer detected') def check_child_safety(self, text): """Critical: Child safety violations""" text_lower = text.lower() child_terms = ['child', 'minor', 'kid', 'teen', 'teenager', 'underage', 'student', 'pupil'] inappropriate_context = ['date', 'dating', 'romantic', 'relationship', 'meet in person', 'alone', 'secret', 'don\'t tell', 'special friend'] has_child_term = any(term in text_lower for term in child_terms) has_inappropriate = any(term in text_lower for term in inappropriate_context) if has_child_term and has_inappropriate: self.add_violation('CHILD_SAFETY_CRITICAL', 3, 'Child safety violation - REPORT REQUIRED') def check_malicious_patterns(self, text): """Detect malware and hacking patterns""" text_lower = text.lower() malicious_patterns = [ (r'(click|open).{0,20}attachment.{0,20}(urgent|important|invoice)', 'MALICIOUS_ATTACHMENT', 2), (r'(download|install|run).{0,20}(software|program|tool|update)', 'UNAUTHORIZED_SOFTWARE', 2), (r'(disable|turn off).{0,20}(antivirus|firewall|security)', 'SECURITY_BYPASS', 3), (r'(admin|administrator|root).{0,20}(access|password|privileges)', 'PRIVILEGE_ESCALATION', 3), ] for pattern, violation_type, severity in malicious_patterns: if re.search(pattern, text_lower): self.add_violation(violation_type, severity, pattern) def add_violation(self, violation_type, severity, pattern): """Record a security violation""" self.violations.append({ 'type': violation_type, 'severity': severity, 'pattern': pattern, 'timestamp': datetime.now().isoformat() }) if severity > self.threat_level: self.threat_level = severity def add_warning(self, warning_type, message): """Record a warning""" self.warnings.append({ 'type': warning_type, 'message': message }) if self.threat_level == 0: self.threat_level = 1 def generate_report(self): """Generate security scan report""" return { 'threat_level': self.threat_level, 'status': self.get_status(), 'violations': self.violations, 'warnings': self.warnings, 'summary': self.get_summary() } def get_status(self): """Get security status""" if self.threat_level >= 3: return 'CRITICAL_BLOCK_AND_REPORT' elif self.threat_level == 2: return 'BLOCK' elif self.threat_level == 1: return 'WARNING' else: return 'SAFE' def get_summary(self): """Get human-readable summary""" if self.threat_level >= 3: return f"🚨 CRITICAL: {len(self.violations)} severe violations detected. DO NOT SEND. REPORT REQUIRED." elif self.threat_level == 2: return f"🛑 BLOCKED: {len(self.violations)} violations detected. Cannot format this email." elif self.threat_level == 1: return f"⚠️ WARNING: {len(self.warnings)} potential issues detected. Review carefully." else: return "✅ No security issues detected." if __name__ == "__main__": if len(sys.argv) < 2: print("Usage: python3 security_scan.py 'email text'") sys.exit(1) scanner = SecurityScanner() report = scanner.scan(sys.argv[1]) # Print report print(f"\n{'='*60}") print(f"SECURITY SCAN REPORT") print(f"{'='*60}") print(f"Status: {report['status']}") print(f"Threat Level: {report['threat_level']}/3") print(f"\n{report['summary']}\n") if report['violations']: print("VIOLATIONS:") for v in report['violations']: severity_icon = "🚨" if v['severity'] >= 3 else "🛑" print(f" {severity_icon} {v['type']}") print(f" Pattern: {v['pattern'][:50]}...") if report['warnings']: print("\nWARNINGS:") for w in report['warnings']: print(f" ⚠️ {w['type']}: {w['message']}") print(f"\n{'='*60}\n") # Return appropriate exit code sys.exit(report['threat_level'])

#!/bin/bash # Email Formatter - Secure Processing Pipeline # This workflow is REQUIRED for every email formatting request set -e # Exit on any error EMAIL_TEXT="$1" TEMP_DIR="/tmp/email-formatter-$$" mkdir -p "$TEMP_DIR" echo "🔒 Starting Secure Email Processing Pipeline..." echo "================================================" # STEP 1: PRE-FLIGHT SECURITY SCAN (CRITICAL) echo "Step 1/7: Running security scan..." python3 ~/.email-formatter-skill/scripts/security_scan.py "$EMAIL_TEXT" SECURITY_EXIT=$? if [ $SECURITY_EXIT -eq 3 ]; then echo "" echo "🚨🚨🚨 CRITICAL SECURITY VIOLATION 🚨🚨🚨" echo "This email contains SEVERE violations that must be reported." echo "Formatting REFUSED. Potential illegal activity detected." echo "" echo "ACTIONS REQUIRED:" echo "1. Do NOT send this email" echo "2. Document the incident" echo "3. Report to appropriate authorities if applicable" echo "4. Inform user of violation" exit 3 elif [ $SECURITY_EXIT -eq 2 ]; then echo "" echo "🛑 SECURITY BLOCK" echo "This email violates safety policies and cannot be formatted." echo "Review the security report above for specific violations." echo "" echo "SUGGESTED ACTIONS:" echo "1. Identify the specific violation" echo "2. Explain to user why it's blocked" echo "3. Suggest legitimate alternatives" echo "4. Offer to help rewrite with appropriate content" exit 2 elif [ $SECURITY_EXIT -eq 1 ]; then echo "" echo "⚠️ SECURITY WARNING" echo "Potential issues detected. Proceeding with caution..." echo "Will re-scan after formatting to ensure no issues introduced." echo "" fi # STEP 2: CONTENT ANALYSIS echo "" echo "Step 2/7: Analyzing content..." echo "$EMAIL_TEXT" > "$TEMP_DIR/original.txt" # Word count WORD_COUNT=$(echo "$EMAIL_TEXT" | wc -w) echo " 📊 Word count: $WORD_COUNT" if [ $WORD_COUNT -gt 500 ]; then echo " ⚠️ Email is very long. Consider breaking into multiple emails." fi # STEP 3: TONE ANALYSIS echo "" echo "Step 3/7: Analyzing tone..." python3 ~/.email-formatter-skill/scripts/tone_analyzer.py "$EMAIL_TEXT" > "$TEMP_DIR/tone.txt" cat "$TEMP_DIR/tone.txt" # Check if tone is aggressive if grep -q "AGGRESSIVE" "$TEMP_DIR/tone.txt"; then echo "" echo " ⚠️ AGGRESSIVE TONE DETECTED" echo " Recommendation: Suggest user wait 24 hours before sending" echo " Offer to rewrite in professional, constructive tone" echo "" read -p " Continue anyway? (yes/no): " CONTINUE if [ "$CONTINUE" != "yes" ]; then echo " Formatting cancelled by tone check." exit 1 fi fi # STEP 4: GRAMMAR CHECK echo "" echo "Step 4/7: Checking grammar..." python3 ~/.email-formatter-skill/scripts/grammar_check.py "$EMAIL_TEXT" # STEP 5: READABILITY ANALYSIS echo "" echo "Step 5/7: Analyzing readability..." python3 ~/.email-formatter-skill/scripts/readability.py "$EMAIL_TEXT" > "$TEMP_DIR/readability.txt" cat "$TEMP_DIR/readability.txt" # STEP 6: FORMAT THE EMAIL echo "" echo "Step 6/7: Formatting email..." echo " [Agent applies formatting rules based on guidelines]" # ... AI agent performs formatting here ... # FORMATTED_EMAIL="..." # STEP 7: POST-FORMATTING SECURITY RE-SCAN (CRITICAL) echo "" echo "Step 7/7: Final security validation..." python3 ~/.email-formatter-skill/scripts/security_scan.py "$FORMATTED_EMAIL" FINAL_SECURITY=$? if [ $FINAL_SECURITY -ne 0 ]; then echo "" echo "🚨 POST-FORMATTING SECURITY FAILURE" echo "Formatted version introduced security issues!" echo "This should never happen - formatting logic has a bug." echo "Reverting to original and blocking output." exit 2 fi # SUCCESS echo "" echo "✅ All security checks passed" echo "✅ Email formatted successfully" echo "" echo "================================================" echo "FORMATTED EMAIL READY FOR REVIEW" echo "================================================" # Cleanup rm -rf "$TEMP_DIR"

name	email-formatter
description	Transform rough email drafts into polished, professional messages. Use this skill when the user wants to improve email quality, fix grammar and tone, format business emails, or convert casual messages into professional communication. Triggers include: 'format my email', 'make this professional', 'improve this message', 'fix my email', 'polish this draft', or any request to enhance email writing quality. Also use when converting bullet points or notes into complete emails, adjusting tone (formal/casual/friendly), or preparing important messages for clients, managers, or stakeholders.
license	MIT
author	Your Name
version	1.0.0

email-formatter

Informações da origem

Opções de instalação

Revise os arquivos de origem

Mais deste repositório

Email Formatter - Professional Email Enhancement

Installation & Setup

Prerequisites Check

Auto-Installation Script

Mais deste repositório

Email Formatter - Professional Email Enhancement

Installation & Setup

Prerequisites Check

Auto-Installation Script

Manual Installation (if auto-install fails)

Verify Installation

Dependencies

Required (Always Available)

Optional (Enhanced Features)

Overview

⚠️ CRITICAL SECURITY & SAFETY REQUIREMENTS

SECURITY LEVEL: MAXIMUM - Multi-Layer Validation Required

Layer 1: Content Classification (BLOCK IMMEDIATELY)

Layer 2: Pattern Recognition (RED FLAGS)

Layer 3: Sentiment & Tone Analysis (WARN OR BLOCK)

Layer 4: Context Validation (VERIFY LEGITIMACY)

Layer 5: Privacy & Data Protection (GDPR/CCPA COMPLIANCE)

ZERO TOLERANCE BLOCKING - Immediate Rejection

Enhanced Security Response Protocol

Helper Scripts & Tools

1. Grammar Checker (grammar_check.py)

2. Tone Analyzer (tone_analyzer.py)

3. Readability Scorer (readability.py)

4. Security Scanner (security_scan.py)

Usage Workflow for AI Agents

Critical Enforcement Rules for AI Agents

When to Use This Skill

Core Principles

Formatting Process

Step 1: Analyze the Draft

Step 2: Apply Improvements

Step 3: Polish Details

Common Email Scenarios

1. Request Email

2. Follow-Up Email

3. Bad News Email

4. Introduction Email

Best Practices

DO:

DON'T:

Tone Guide

Quality Checklist

Red Flag Detection

Incident Response Protocol

Security Metrics & Monitoring

Privacy & Data Protection Compliance

Continuous Improvement

Output Format

Special Considerations

Special Considerations

Common Mistakes to Avoid

Advanced Techniques

Version History

License

1. Grammar Checker (`grammar_check.py`)

2. Tone Analyzer (`tone_analyzer.py`)

3. Readability Scorer (`readability.py`)

4. Security Scanner (`security_scan.py`)