Skill: drew2operations/local-business-pack (version 1.0.0)

--- name: local-business-pack description: Automates the four highest-ROI tasks for local service businesses — review management, appointment follow-up, customer reactivation, and competitor monitoring. Built for restaurants, salons, contractors, dentists, and any local service provider. version: 1.0.0 tags: - local-business - reviews - appointment - reactivation - competitor - crm - automation --- # Local Business Pack A complete automation suite for local service businesses. Handles the four revenue-critical workflows that most small business owners either neglect or pay expensive software subscriptions for. ## When to use this skill Use this skill when the user asks about any of the following: - Responding to Google, Yelp, or TripAdvisor reviews - Following up with customers after appointments - Re-engaging lapsed customers who haven't returned - Monitoring what nearby competitors are doing - Writing appointment reminder messages - Handling negative reviews professionally ## Workflow 1: Review Response Engine When a user provides a customer review (positive, neutral, or negative), generate a professional, on-brand response using these rules: ### Positive reviews (4–5 stars) - Open with genuine gratitude (vary the opening — never repeat "Thank you for your review") - Reference a specific detail from the review if one is present - Invite them back with a forward-looking line - Sign off with the business name - Length: 3–5 sentences max - Tone: warm, personal, never corporate ### Neutral reviews (3 stars) - Acknowledge both the positives and the concern - Do not get defensive - Offer a direct path to resolution (call, email, or visit) - Show that feedback is taken seriously - Length: 4–6 sentences ### Negative reviews (1–2 stars) - Never argue or match the customer's tone - Apologize for the experience (not for being wrong — for their frustration) - Take the conversation offline immediately: provide a direct contact - Keep it short: 3–4 sentences max - Do NOT offer discounts or refunds in public responses - Refer to references/review-response-templates.md for tone examples ### Instructions for the agent 1. Ask the user for: the review text, star rating, and business name/type 2. Generate the response using the rules above 3. Offer 2 variations so the user can pick 4. Ask if they want it saved to a responses log file --- ## Workflow 2: Appointment Follow-Up Sequence Generate a 3-message follow-up sequence for after a customer appointment. ### The 3-message structure - **Message 1 (same day, 2 hours after appointment):** Thank you + how did it go? - **Message 2 (3 days later):** Check-in + soft invite to rebook - **Message 3 (14 days later):** Rebook prompt + any current offer ### Rules - Messages must be SMS-length (under 160 characters each) unless user specifies email - Personalize with customer first name placeholder: {first_name} - Include business name in at least one message - Never sound automated — write like a real person texted them - Refer to references/appointment-followup-templates.md for examples by business type ### Instructions for the agent 1. Ask for: business type, service provided, and customer's first name (or use {first_name}) 2. Generate all 3 messages 3. Ask if they want a 4th message at 30 days for rebooking 4. Offer to save the sequence as a reusable template file --- ## Workflow 3: Customer Reactivation Campaign Identify and re-engage customers who haven't visited in 60–180 days. ### Campaign structure (3-message arc) - **Message 1 — "We miss you":** Warm, no pressure, reminds them you exist - **Message 2 (5 days later) — Value add:** Share something useful (tip, update, new service) - **Message 3 (7 days later) — Soft offer:** Time-limited reason to come back ### Rules - Never say "we haven't seen you in a while" (sounds passive-aggressive) - Lead with value, not guilt - The offer in message 3 should feel exclusive, not desperate - Personalize with {first_name} and {last_service} placeholders - Refer to references/reactivation-templates.md for industry-specific examples ### Instructions for the agent 1. Ask for: business type, typical services, and how long since last visit 2. Generate all 3 messages 3. Ask if they want SMS or email format 4. Offer to generate a subject line if email format selected --- ## Workflow 4: Local Competitor Monitor Report Research and summarize what nearby competitors are doing across reviews, pricing signals, and online presence. ### What to research for each competitor - Google Maps rating and recent review trends (improving or declining?) - Most common complaints in their 1–3 star reviews (your opportunity) - Most praised aspects in their 4–5 star reviews (what you're up against) - Whether they're running any visible promotions - Their response rate to reviews (low rate = opportunity to differentiate) ### Output format Produce a clean summary report: ``` COMPETITOR INTELLIGENCE REPORT Business: [name] Location: [city/area] Generated: [date] THEIR STRENGTHS (what customers love) - [bullet] - [bullet] THEIR WEAKNESSES (complaints to learn from) - [bullet] - [bullet] OPPORTUNITIES FOR [your business name] - [bullet] - [bullet] REVIEW RESPONSE BEHAVIOR - Avg rating: X.X - Response rate: X% - Response tone: [professional / defensive / absent] ``` ### Instructions for the agent 1. Ask for: the user's business name, location, and up to 3 competitor names or Google Maps URLs 2. Use web search to pull recent reviews and signals for each 3. Generate one report per competitor 4. End with a "Your Edge" summary — what the user can do THIS WEEK to differentiate --- ## Output and file management - Save all generated content to ~/Documents/drew2_workspace/output/[business-name]/ - Create subdirectories: reviews/, sequences/, reports/ - Name files by date: YYYY-MM-DD-type.md - Always confirm save location with user before writing ## Tone guidelines - Human, not robotic - Confident, not pushy - Specific, not generic - Local businesses are often run by real people under real stress — be efficient and practical


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)