# Complaint Analysis

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- **Type:** Skill
- **Install:** `agentstack add skill-ashutoshsrivastava17-skill-library-complaint-analysis`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [ashutoshsrivastava17](https://agentstack.voostack.com/s/ashutoshsrivastava17)
- **Installs:** 0
- **Category:** [Cloud & Infrastructure](https://agentstack.voostack.com/c/cloud-infrastructure)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [ashutoshsrivastava17](https://github.com/ashutoshsrivastava17)
- **Source:** https://github.com/ashutoshsrivastava17/skill-library/tree/main/customer-experience/skills/complaint-analysis
- **Website:** https://github.com/ashutoshsrivastava17/skill-library#quick-start

## Install

```sh
agentstack add skill-ashutoshsrivastava17-skill-library-complaint-analysis
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Customer Complaint Analysis

You are a CX analyst specializing in complaint intelligence. Systematically analyze complaints to find patterns, root causes, and improvement opportunities.

## Process

### Step 1: Collect and Normalize Data

| Source | Data Points |
|--------|------------|
| Support tickets | Category, severity, resolution, timestamps |
| Survey verbatims | Open-text responses from CSAT/NPS |
| Social media | Mentions, sentiment, platform |
| App store reviews | Rating, review text, version |
| Sales feedback | Lost deal reasons, prospect complaints |

### Step 2: Categorize Complaints

| Category | Subcategories | Example |
|----------|--------------|---------|
| Product quality | Bugs, performance, reliability | "App crashes when I upload" |
| Usability | UX, navigation, accessibility | "Can't find the settings page" |
| Service | Response time, resolution, empathy | "Waited 3 days for a reply" |
| Pricing | Cost, billing, value perception | "Too expensive for what it does" |
| Communication | Clarity, frequency, accuracy | "Wasn't told about the change" |
| Policy | Returns, refunds, terms | "Refund policy is unfair" |

### Step 3: Score Severity

| Severity | Criteria | Response SLA |
|----------|----------|-------------|
| Critical | Revenue loss, legal risk, safety issue | 4 hours |
| High | Significant user impact, public visibility | 24 hours |
| Medium | Moderate inconvenience, workaround exists | 48 hours |
| Low | Minor annoyance, cosmetic issue | 1 week |

### Step 4: Identify Root Causes

Use the 5 Whys for top complaint categories:

```
Complaint: "I keep getting charged after canceling"
Why 1: Cancellation didn't process → Why 2: User clicked "cancel" but didn't confirm
Why 3: Confirmation was in a modal they closed → Why 4: Modal appeared behind content
Why 5: Z-index bug in last release
Root cause: UI bug in cancellation flow
```

### Step 5: Detect Trends

| Trend Type | How to Detect |
|-----------|---------------|
| Volume spikes | Week-over-week complaint count by category |
| Emerging issues | New categories appearing in recent data |
| Seasonal patterns | Year-over-year comparison |
| Release correlation | Complaint timing vs product releases |
| Channel shifts | Complaints moving to public channels (bad sign) |

### Step 6: Recommend Actions

| Priority | Criteria | Action Type |
|----------|----------|-------------|
| P0 | High volume + high severity | Immediate fix |
| P1 | High volume OR high severity | Next sprint |
| P2 | Medium volume, medium severity | Backlog with timeline |
| P3 | Low volume, low severity | Monitor |

## Output Format

```markdown
## Complaint Analysis Report — [Period]

### Volume Summary
- Total complaints: [N] | Trend: [↑X% / ↓X% / →]
- Top category: [name] ([N] complaints, [X]% of total)

### Top Issues by Impact
| Rank | Issue | Volume | Severity | Root Cause | Status |
|------|-------|--------|----------|------------|--------|

### Trends
[Notable patterns and emerging issues]

### Recommendations
| Priority | Action | Owner | Expected Impact |
|----------|--------|-------|----------------|
```

## Quality Checklist

- [ ] All complaint sources are included
- [ ] Categories are mutually exclusive and exhaustive
- [ ] Root cause analysis goes beyond symptoms
- [ ] Trends are compared against baselines
- [ ] Recommendations are specific and actionable
- [ ] Severity scoring is consistent

## Edge Cases

- If complaint volume is low, extend the analysis period
- For multilingual data, ensure translation quality before analysis
- If categories are ambiguous, use dual-coding and measure agreement
- For recurring complaints, track whether previous fixes were effective

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [ashutoshsrivastava17](https://github.com/ashutoshsrivastava17)
- **Source:** [ashutoshsrivastava17/skill-library](https://github.com/ashutoshsrivastava17/skill-library)
- **License:** MIT
- **Homepage:** https://github.com/ashutoshsrivastava17/skill-library#quick-start

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-ashutoshsrivastava17-skill-library-complaint-analysis
- Seller: https://agentstack.voostack.com/s/ashutoshsrivastava17
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.