Agent skill

Cashclaw Reputation Manager

by ertugrulakben in ertugrulakben/cashclaw

Monitors online reviews, generates professional response drafts, and creates reputation reports.

MITAuto-check passedSales & Support

Install Cashclaw Reputation Manager

skills CLI
$ npx skills add ertugrulakben/cashclaw --skill cashclaw-reputation-manager -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ertugrulakben/cashclaw cashclaw-reputation-manager --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ertugrulakben/cashclaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cashclaw-reputation-manager .claude/skills/cashclaw-reputation-manager && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cashclaw-reputation-manager
GitHub stars
303
Token cost
~3k tokens
SKILL.md length
414 words
Files
1
Skills in repo
13
Repo updated
First seen
Licence
MIT

At a glance

Monitors online reviews, generates professional response drafts, and creates reputation reports.

  • Works in 5 steps: Platform Discovery → Review Aggregation → Sentiment Analysis → …
  • Tasks that involve Customer feedback analysis
  • SKILL.md covers Pricing Tiers, Reputation Management Workflow, Quality Checklist and Deliverable Format, plus 3 more sections
  • Reaches acme.com

What it does

Cashclaw Reputation Manager is an agent skill from ertugrulakben/cashclaw. Monitors online reviews, generates professional response drafts, and creates reputation reports. Covers review aggregation, sentiment analysis, and strategic response planning across major platforms.

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Sales & Support, covering Customer feedback analysis. The repository describes itself as: The Agent Economy Layer — agents earn, agents spend, Guard protects. 13 skills, runtime cost cap, recursive kill, tool firewall. 50+ HYRVE API endpoints, job polling daemon, MPP…. The licence is MIT.

When your agent uses it

  • Tasks that involve Customer feedback analysis

Example prompts

  • “Use the cashclaw-reputation-manager skill to monitor online reviews, generates professional response drafts, and creates reputation reports”
  • “/cashclaw-reputation-manager”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Platform Discovery
  2. Review Aggregation
  3. Sentiment Analysis
  4. Response Drafting (Standard and Pro)
  5. Reputation Report Assembly

What it can do on your machine

Read from SKILL.md and the folder at commit ff30cb3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown, yaml, json and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • acme.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cashclaw Reputation Manager loads about 3k tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 414 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ertugrulakben/cashclaw at commit ff30cb3, republished under its MIT licence (© ertugrulakben). 414 words, ~3,043 tokens.

Download SKILL.mdSave it as .claude/skills/cashclaw-reputation-manager/SKILL.md (or your agent's skills folder).
name
cashclaw-reputation-manager
description
Monitors online reviews, generates professional response drafts, and creates reputation reports. Covers review aggregation, sentiment analysis, and strategic response planning across major platforms.

CashClaw Reputation Manager

You manage online reputation professionally. Every audit must be thorough, every response draft must be empathetic and strategic, and every report must give the client a clear picture of their online standing. Generic "thank you for your feedback" responses are unacceptable -- every reply must address the specific review content.

Pricing Tiers

TierScopePriceDelivery
BasicReputation audit only (snapshot report)$196 hours
StandardAudit + response drafts for all negative/neutral reviews$3512 hours
ProFull monthly monitoring + responses + strategy recommendations$4948 hours

Reputation Management Workflow

Step 1: Platform Discovery

Identify all platforms where the client has a public presence:

yaml
Platform Checklist:
  General Review Sites:
    - [ ] Google Business Profile
    - [ ] Yelp
    - [ ] Trustpilot
    - [ ] Better Business Bureau (BBB)

  Industry-Specific:
    - [ ] G2 (SaaS/Software)
    - [ ] Capterra (Software)
    - [ ] TripAdvisor (Hospitality)
    - [ ] Healthgrades (Healthcare)
    - [ ] Avvo (Legal)
    - [ ] Zillow (Real Estate)
    - [ ] Clutch (Agencies)
    - [ ] Product Hunt (Tech products)

  Social Media:
    - [ ] Facebook Reviews/Recommendations
    - [ ] LinkedIn Company Page
    - [ ] Twitter/X mentions
    - [ ] Instagram comments
    - [ ] Reddit mentions

  App Stores (if applicable):
    - [ ] Apple App Store
    - [ ] Google Play Store

  Other:
    - [ ] Industry forums
    - [ ] Glassdoor (employer brand)
    - [ ] Indeed (employer brand)

Document which platforms are active, which have unclaimed profiles, and which have no presence. An unclaimed Google Business Profile is a critical finding.

Step 2: Review Aggregation

Collect all reviews from discovered platforms:

json
{
  "platform": "Google",
  "review_id": "{unique_id}",
  "author": "{reviewer_name}",
  "date": "{ISO8601}",
  "rating": 4,
  "rating_max": 5,
  "text": "{full review text}",
  "response_exists": false,
  "response_text": null,
  "sentiment": "positive",
  "topics": ["customer_service", "product_quality"],
  "priority": "low",
  "action_needed": "none"
}

Aggregation Rules:

  • Collect ALL reviews, not just recent ones (last 12 months minimum).
  • For platforms with hundreds of reviews, focus on the last 50 plus all 1-2 star reviews.
  • Record whether the business has responded to each review.
  • Flag reviews that mention specific employees, legal threats, or false claims.
Step 3: Sentiment Analysis

Categorize every review and calculate aggregate scores:

markdown
## Sentiment Breakdown

### Overall Scores
| Platform | Avg Rating | Total Reviews | Response Rate |
|----------|-----------|---------------|---------------|
| Google | 4.2/5 | 127 | 45% |
| Yelp | 3.8/5 | 43 | 12% |
| Trustpilot | 4.5/5 | 89 | 78% |
| **Weighted Average** | **4.2/5** | **259** | **45%** |

### Sentiment Distribution
| Sentiment | Count | Percentage |
|-----------|-------|------------|
| Positive (4-5 stars) | 198 | 76% |
| Neutral (3 stars) | 31 | 12% |
| Negative (1-2 stars) | 30 | 12% |

### Topic Analysis
| Topic | Mentions | Avg Sentiment |
|-------|----------|---------------|
| Customer Service | 89 | Positive |
| Product Quality | 72 | Positive |
| Pricing | 45 | Mixed |
| Delivery/Speed | 38 | Negative |
| Support Response Time | 29 | Negative |

Sentiment Classification Rules:

  • 5 stars with positive text = Positive
  • 4 stars = Positive (unless text is mostly negative)
  • 3 stars = Neutral
  • 2 stars = Negative
  • 1 star = Negative
  • Text overrides star rating when they conflict
Show full SKILL.md (183 more words)Show less
Step 4: Response Drafting (Standard and Pro)

Write professional response drafts for every unanswered negative and neutral review.

Response Framework by Rating:

1-2 Star Reviews (Negative):

markdown
Structure:
1. Acknowledge - Thank them for the feedback (not generic).
2. Empathize - Show you understand why they are frustrated.
3. Address - Respond to the specific issue they raised.
4. Resolve - Offer a concrete next step (not "call us").
5. Offline - Move the conversation to a private channel.

Tone: Professional, empathetic, never defensive.
Length: 60-120 words.

Example:

Hi {name}, thank you for sharing your experience. I understand how
frustrating it must be to {specific issue from review}. That is not
the standard we hold ourselves to. Our {role} team has looked into
this and {specific action taken or explanation}. I would like to make
this right -- could you reach out to me directly at {email} so we
can resolve this for you? - {Manager Name}, {Title}

3 Star Reviews (Neutral):

markdown
Structure:
1. Thank - Genuine appreciation for balanced feedback.
2. Highlight - Acknowledge what they liked.
3. Address - Respond to the criticism constructively.
4. Invite - Ask them to give you another chance.

Tone: Warm, constructive, forward-looking.
Length: 50-90 words.

4-5 Star Reviews (Positive):

markdown
Structure:
1. Thank - Specific, not generic.
2. Reinforce - Reference something specific they mentioned.
3. Invite - Encourage them to share or return.

Tone: Grateful, personal, brief.
Length: 30-60 words.

Response Rules (apply to every response):

yaml
ALWAYS:
  - Address the reviewer by name
  - Reference specific details from their review
  - Take ownership of mistakes (never blame the customer)
  - Provide a concrete resolution path
  - Sign with a real person's name and title
  - Respond within 24-48 hours of the review

NEVER:
  - Use the same template for multiple responses
  - Be defensive or argumentative
  - Share private customer details publicly
  - Offer compensation publicly (do this offline)
  - Accuse the reviewer of lying
  - Use corporate jargon ("we value your feedback" alone is insufficient)
  - Respond to fake reviews without flagging them first
Step 5: Reputation Report Assembly

Generate the comprehensive report:

markdown
# Online Reputation Report

**Brand:** {brand_name}
**Date:** {date}
**Tier:** {Basic|Standard|Pro}
**Platforms Analyzed:** {count}

---

## Executive Summary
{3-5 sentences: overall health, critical findings, top recommendation}

## Reputation Score Card
| Metric | Score | Benchmark | Status |
|--------|-------|-----------|--------|
| Overall Rating | 4.2/5 | 4.0+ | GOOD |
| Response Rate | 45% | 80%+ | NEEDS WORK |
| Sentiment Ratio | 76% positive | 70%+ | GOOD |
| Review Volume (monthly) | 12 | 15+ | FAIR |
| Platform Coverage | 4/8 | 6/8 | NEEDS WORK |

## Platform-by-Platform Analysis
{Detailed breakdown per platform}

## Sentiment Analysis
{Topic analysis with trends}

## Critical Reviews Requiring Immediate Response
{Top 5 most urgent unanswered negative reviews with draft responses}

## Response Drafts (Standard/Pro)
{All drafted responses organized by platform and priority}

## Trend Analysis (Pro)
{Rating trend over time: improving, stable, declining}
{Seasonal patterns if observable}
{Impact of response strategy on subsequent reviews}

## Strategic Recommendations
1. {Highest-impact recommendation}
2. {Second recommendation}
3. {Third recommendation}
4. {Fourth recommendation}
5. {Fifth recommendation}

## Action Plan
| Action | Priority | Effort | Expected Impact |
|--------|----------|--------|-----------------|
| {action1} | High | Low | +0.3 rating |
| {action2} | High | Medium | +15% response rate |
| {action3} | Medium | Low | +5 reviews/month |

---
*Generated by CashClaw Reputation Manager | cashclaw.ai*

Quality Checklist

Before delivering, verify:

[ ] All major review platforms have been checked
[ ] Review counts and ratings match the actual platform data
[ ] Sentiment analysis covers the last 12 months minimum
[ ] Every response draft addresses the specific review content
[ ] No two response drafts use the same opening line
[ ] Response drafts are signed with a name and title placeholder
[ ] Negative review responses include a concrete resolution step
[ ] No private customer information in response drafts
[ ] Topic analysis includes at least 5 identified themes
[ ] Recommendations are specific and actionable
[ ] Executive summary can stand alone as a decision document
[ ] Platform coverage is complete (no major platform missed)
[ ] Unclaimed profiles are flagged as critical findings
[ ] Response rate calculation is accurate
[ ] Report formatting is consistent throughout

Deliverable Format

Every reputation management delivery includes:

deliverables/
  reputation-report-{brand}-{date}.md   - Full reputation analysis
  review-responses.md                    - All drafted responses (Standard/Pro)
  brief-summary.md                       - Executive summary for quick review
review-responses.md Format
markdown
# Review Response Drafts

**Brand:** {brand_name}
**Date:** {date}
**Total Responses Drafted:** {count}

## Priority: HIGH (respond within 24 hours)

### Google - 1 Star - {reviewer_name} - {date}
**Review:** "{review text excerpt}"
**Draft Response:**
> {response draft}

### Yelp - 2 Stars - {reviewer_name} - {date}
**Review:** "{review text excerpt}"
**Draft Response:**
> {response draft}

## Priority: MEDIUM (respond within 48 hours)

### Google - 3 Stars - {reviewer_name} - {date}
**Review:** "{review text excerpt}"
**Draft Response:**
> {response draft}

## Priority: LOW (respond within 1 week)

### Trustpilot - 4 Stars - {reviewer_name} - {date}
**Review:** "{review text excerpt}"
**Draft Response:**
> {response draft}

Monthly Monitoring Setup (Pro Tier)

For Pro tier clients, set up ongoing monitoring:

yaml
Monitoring Config:
  Brand: "{brand_name}"
  Check Frequency: "weekly"
  Platforms:
    - google_business
    - yelp
    - trustpilot
    - facebook
    - g2

  Alerts:
    new_negative_review: "immediate"
    rating_drop_threshold: 0.2
    new_platform_mention: "daily_digest"

  Monthly Deliverables:
    - Updated reputation scorecard
    - New review response drafts
    - Trend analysis (month-over-month)
    - Competitor reputation comparison
    - Adjusted strategy recommendations

Quality Standards

  • Every response draft must be unique -- no copy-paste templates across reviews.
  • Sentiment classification must be verifiable against the actual review text.
  • Never inflate ratings or misrepresent review counts. Report what you find.
  • If a platform has no reviews, report it as zero, not as missing data.
  • Fake review detection: Flag reviews with suspicious patterns (burst of 5-star reviews, generic language, reviewer with no other activity) but never accuse publicly.
  • Response drafts must be ready to post -- not outlines, not bullet points.
  • Pro tier trend analysis must cover at least 6 months of data if available.
  • Recommendations must be prioritized by effort-to-impact ratio.

Example Commands

bash
# Run a basic reputation audit
cashclaw reputation --brand "Acme Corp" --url "https://acme.com" --tier basic

# Audit with response drafts
cashclaw reputation --brand "Acme Corp" --url "https://acme.com" --tier standard --responses

# Full pro monitoring setup
cashclaw reputation --brand "Acme Corp" --url "https://acme.com" --tier pro --monitor monthly

# Generate responses for new reviews only
cashclaw reputation respond --brand "Acme Corp" --since "2026-03-01" --output responses.md

# Check reputation score trend
cashclaw reputation trend --brand "Acme Corp" --months 6

© ertugrulakben, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/cashclaw-reputation-manager of ertugrulakben/cashclaw.

Open the folder on GitHubat commit ff30cb3

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Categories

Questions about Cashclaw Reputation Manager

What does Cashclaw Reputation Manager do?

Monitors online reviews, generates professional response drafts, and creates reputation reports. Cashclaw Reputation Manager is an agent skill from ertugrulakben/cashclaw. Monitors online reviews, generates professional response drafts, and creates reputation reports.

When should I use Cashclaw Reputation Manager?

Cashclaw Reputation Manager fits situations like: tasks that involve Customer feedback analysis.

How do I install Cashclaw Reputation Manager in Claude Code?

Run `npx skills add ertugrulakben/cashclaw --skill cashclaw-reputation-manager -a claude-code`. Or copy the skill folder (skills/cashclaw-reputation-manager in ertugrulakben/cashclaw) into .claude/skills/cashclaw-reputation-manager in your project. Claude Code loads it when a task matches its description.

How do I install Cashclaw Reputation Manager in Codex?

Run `npx skills add ertugrulakben/cashclaw --skill cashclaw-reputation-manager -a codex`. Or copy the skill folder (skills/cashclaw-reputation-manager in ertugrulakben/cashclaw) into .agents/skills/cashclaw-reputation-manager in your project. Codex loads it when a task matches its description.

Can I use Cashclaw Reputation Manager in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ertugrulakben/cashclaw --skill cashclaw-reputation-manager -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cashclaw-reputation-manager, .gemini/skills/cashclaw-reputation-manager, .github/skills/cashclaw-reputation-manager and .opencode/skills/cashclaw-reputation-manager in your project.

What does Cashclaw Reputation Manager need to run?

SKILL.md names no scripts, command-line tools or credentials: Cashclaw Reputation Manager is instructions for the agent only.

Does Cashclaw Reputation Manager access the network?

SKILL.md names 1 domain. In commands or code: acme.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Cashclaw Reputation Manager safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Cashclaw Reputation Manager use?

Cashclaw Reputation Manager is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cashclaw Reputation Manager use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Cashclaw Reputation Manager?

Skills that share tags, products or a category with Cashclaw Reputation Manager: Review Analysis (liangdabiao/amazon-sorftime-research-MCP-skill, 959 stars), Bggg Data Amazon (binggandata/bggg-skills, 605 stars), Zsxq (unnoo/zsxq-skill, 304 stars) and Roadtrip Navigator (Waybox-AI/roadtrip-skill, 126 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cashclaw Reputation Manager?

ertugrulakben (a GitHub user) maintains it in ertugrulakben/cashclaw, which has 303 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 6, 2026.

Source: ertugrulakben/cashclaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.