# Reputation Quick > 60-Second Reputation Scorecard - Skill: `zubair-trabzada/reputation-quick` (Agent Skill) - Install (CLI): `npx skillmds@latest add zubair-trabzada/reputation-quick` - Raw SKILL.md: https://api.skillmd.com/api/skills/zubair-trabzada/reputation-quick/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: zubair-trabzada (https://skillmd.com/u/zubair-trabzada) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/zubair-trabzada/reputation-quick --- # 60-Second Reputation Scorecard ## Skill Purpose Generate a fast, high-level reputation scorecard for a business in under 60 seconds. This is the quick triage version of the full audit -- designed for rapid evaluation, comparing multiple businesses, or getting a snapshot before deciding whether a deep dive is warranted. Returns an overall score, star rating averages, review volume, sentiment ratio, top complaint and praise themes, and a one-line recommendation. ## When to Use - User wants a quick reputation check without a full audit - User is evaluating multiple businesses and needs fast comparisons - User wants to triage which businesses need deeper analysis - User asks for a "quick look" or "snapshot" of reputation - User is vetting a potential partner, vendor, or acquisition target - Triggered by `/reputation quick ` ## How to Execute ### Step 1: Rapid Data Collection Speed is the priority. Run the minimum searches needed for a meaningful scorecard. **Core searches (execute all in parallel via WebSearch):** ``` Search 1: "[Business Name]" reviews Search 2: "[Business Name]" site:google.com/maps (Google reviews) Search 3: "[Business Name]" site:yelp.com Search 4: "[Business Name]" (complaint OR terrible OR scam OR avoid) Search 5: "[Business Name]" (amazing OR love OR recommend OR best) ``` **Data points to extract rapidly:** | Data Point | Source | How to Find | |---|---|---| | Google star rating | Google Maps / Knowledge Panel | Search result 1 or 2 | | Google review count | Google Maps / Knowledge Panel | Same as above | | Yelp star rating | Yelp listing | Search result 3 | | Yelp review count | Yelp listing | Same as above | | Other platform ratings | Search results | Search result 1 | | Negative signal volume | Search result 4 | Count and scan negative results | | Positive signal volume | Search result 5 | Count and scan positive results | | Overall search sentiment | All results | Quick scan of page 1 titles and snippets | ### Step 2: Score Calculation Calculate the Overall Reputation Score (0-100) using this weighted formula: **Component Scores:** | Component | Weight | How to Score | Scoring Guide | |---|---|---|---| | Star Rating Average | 30% | Average star rating across found platforms, normalized to 0-100 | 5.0 stars = 100, 4.5 = 90, 4.0 = 80, 3.5 = 65, 3.0 = 50, 2.5 = 35, 2.0 = 20, 1.5 = 10, 1.0 = 0 | | Review Volume | 15% | Total reviews across all platforms | 500+ = 100, 200-499 = 85, 100-199 = 70, 50-99 = 55, 20-49 = 40, 10-19 = 25, 1-9 = 15, 0 = 0 | | Sentiment Ratio | 25% | Ratio of positive to negative search results on page 1 | All positive = 100, 90%+ positive = 85, 70-89% = 70, 50-69% = 50, 30-49% = 30, <30% = 10 | | Search Result Health | 15% | Quality and sentiment of top 10 branded search results | 9-10 positive/neutral = 100, 7-8 = 80, 5-6 = 60, 3-4 = 40, 1-2 = 20, 0 = 0 | | Recency and Velocity | 15% | How recent are reviews, and are they coming in regularly | Active within last month with steady flow = 100, Last 3 months = 75, Last 6 months = 50, Last year = 30, Older = 10 | **Overall Score = (Star Rating * 0.30) + (Review Volume * 0.15) + (Sentiment * 0.25) + (Search Health * 0.15) + (Recency * 0.15)** **Score Interpretation:** | Score | Grade | Label | Meaning | |---|---|---|---| | 90-100 | A+ | Exceptional | Dominant positive reputation. Minimal risk. | | 80-89 | A | Excellent | Strong reputation with minor room for improvement. | | 70-79 | B | Good | Solid reputation. Some areas to strengthen. | | 60-69 | C+ | Fair | Acceptable but notable gaps or concerns. | | 50-59 | C | Mediocre | Mixed reputation. Needs active management. | | 40-49 | D | Poor | Significant reputation problems. Intervention needed. | | 30-39 | D- | Very Poor | Major reputation damage. Urgent action required. | | 0-29 | F | Critical | Reputation crisis. Immediate professional intervention recommended. | ### Step 3: Theme Identification Quickly scan the search results to identify the single most prominent positive and negative themes. **Common Positive Themes:** - Great customer service / friendly staff - High quality product or service - Good value for money / fair pricing - Professional and reliable - Fast response time / quick delivery - Clean facility / great atmosphere - Knowledgeable and helpful team - Easy to work with / seamless experience **Common Negative Themes:** - Poor customer service / rude staff - Long wait times / slow response - Overpriced / hidden fees / billing issues - Quality issues / product defects - Broken promises / misleading marketing - Difficulty getting refunds or cancellations - Dirty facility / poor maintenance - Management issues / unresponsive to complaints Select the ONE top theme for each (positive and negative) based on frequency in the search results scanned. ### Step 4: One-Line Recommendation Based on the overall score and findings, generate a single actionable recommendation. **Recommendation Templates by Score Range:** | Score Range | Recommendation Focus | |---|---| | 90-100 | Maintain momentum: "Continue current review generation strategy and consider leveraging your strong reputation in marketing materials." | | 80-89 | Optimize gaps: "Address [specific gap] to move from good to exceptional -- focus on [specific platform or theme]." | | 70-79 | Strengthen weaknesses: "Increase review volume on [platform] and proactively address [complaint theme] to strengthen overall perception." | | 60-69 | Active intervention: "Prioritize responding to negative reviews on [platform] and launch a systematic review request campaign to improve your [X]-star average." | | 50-59 | Significant work needed: "Implement a review response strategy immediately and address the recurring [complaint theme] at the operational level before soliciting new reviews." | | 40-49 | Urgent action: "Stop the bleeding -- respond to all unanswered negative reviews within 48 hours and fix the underlying [issue] causing complaints." | | 30-39 | Crisis management: "Consider running `/reputation crisis` -- your reputation needs immediate professional attention focused on [primary issue]." | | 0-29 | Full intervention: "Reputation crisis detected. Run `/reputation audit` for a complete analysis and action plan. Prioritize legal review if defamatory content is present." | ### Step 5: Comparison Mode (Optional) If the user provides multiple business names, generate a comparison table. **Comparison Scorecard:** | Metric | Business A | Business B | Business C | |---|---|---|---| | Overall Score | [X]/100 | [X]/100 | [X]/100 | | Grade | [A-F] | [A-F] | [A-F] | | Google Rating | [X] stars ([N]) | [X] stars ([N]) | [X] stars ([N]) | | Yelp Rating | [X] stars ([N]) | [X] stars ([N]) | [X] stars ([N]) | | Sentiment Ratio | [+/N/-] | [+/N/-] | [+/N/-] | | Top Praise | [theme] | [theme] | [theme] | | Top Complaint | [theme] | [theme] | [theme] | | Recommendation | [one-line] | [one-line] | [one-line] | --- ## Output Format Generate a file called `REPUTATION-SCORECARD-[business-name].md`: ```markdown # Reputation Scorecard ## [Business Name] ### Quick Scan: [Date] --- ## Overall Reputation Score: [X]/100 ([Grade]) --- ## Star Ratings | Platform | Rating | Reviews | Status | |---|---|---|---| | Google | [X.X] stars | [N] reviews | [Emoji-free status: Strong / Adequate / Weak / Critical / Not Found] | | Yelp | [X.X] stars | [N] reviews | [status] | | [Other] | [X.X] stars | [N] reviews | [status] | | **Average** | **[X.X] stars** | **[N] total** | | --- ## Sentiment Snapshot | Sentiment | Percentage | |---|---| | Positive | [X]% | | Neutral | [X]% | | Negative | [X]% | **Sentiment Ratio: [X] positive for every 1 negative** --- ## Score Breakdown | Component | Score | Weight | Weighted | |---|---|---|---| | Star Rating Average | [X]/100 | 30% | [X] | | Review Volume | [X]/100 | 15% | [X] | | Sentiment Ratio | [X]/100 | 25% | [X] | | Search Result Health | [X]/100 | 15% | [X] | | Recency and Velocity | [X]/100 | 15% | [X] | | **Overall** | | | **[X]/100** | --- ## Top Themes **What customers love most:** [Theme with brief evidence] **What customers complain about most:** [Theme with brief evidence] --- ## One-Line Recommendation > [Single actionable recommendation] --- ## Need More Detail? - Run `/reputation audit [business name]` for a comprehensive analysis - Run `/reputation respond [business name]` for review response templates - Run `/reputation social [business name]` for social media reputation scan - Run `/reputation seo [business name]` for search result optimization ``` --- ## Terminal Output The terminal output IS the scorecard for quick scanning. This is the primary output -- the file is secondary. ``` ================================================ REPUTATION SCORECARD: [Business Name] ================================================ Overall Score: [XX]/100 ([Grade]) Star Ratings: Google: [X.X] stars ([N] reviews) Yelp: [X.X] stars ([N] reviews) [Other]: [X.X] stars ([N] reviews) Average: [X.X] stars ([N] total reviews) Sentiment: Positive: [XX]% Neutral: [XX]% Negative: [XX]% Top Praise: [Theme] Top Complaint: [Theme] Recommendation: [One-line recommendation] ================================================ Saved to: REPUTATION-SCORECARD-[business].md For full audit: /reputation audit [business] ================================================ ``` **For comparison mode (multiple businesses):** ``` ================================================================= REPUTATION SCORECARD COMPARISON ================================================================= Business Score Grade Stars Reviews Sentiment ---------------------------------------------------------------- [Business A] [XX] [A] [X.X] [NNN] [XX]% pos [Business B] [XX] [B] [X.X] [NNN] [XX]% pos [Business C] [XX] [C] [X.X] [NNN] [XX]% pos Best Overall: [Business A] Most Reviews: [Business B] Best Rated: [Business A] ================================================================= Saved to: REPUTATION-SCORECARD-comparison.md ================================================================= ``` ## Key Principles - Speed over depth. This skill should feel almost instant. If it is taking more than 60-90 seconds of search time, you are doing too much. Save the deep analysis for `/reputation audit`. - The score must be defensible. Every number should map to observable data from the search results. Do not inflate scores to make the user feel good. Honesty builds trust. - The one-line recommendation is the most important output. It should be specific enough to act on immediately. "Improve your reputation" is useless. "Respond to the 12 unanswered 1-star Google reviews from the last 3 months" is actionable. - When data is missing, say so. If a platform has no reviews or the business is not listed, report "Not Found" rather than guessing. Missing data is itself a finding -- low review presence is a reputation gap. - The terminal output is the primary deliverable. Many users will not open the file. Make the terminal summary complete enough to be useful on its own. - The comparison mode is extremely valuable for agencies evaluating clients, investors evaluating targets, or businesses benchmarking against competitors. Make the comparison table scannable at a glance. - This skill is the gateway to deeper analysis. Always include pointers to `/reputation audit` and other skills at the bottom.