# Chatwoot Reporting Analytics

> Analyze Chatwoot metrics — account overview, agent performance, inbox reports, team reports, conversation metrics, and label analytics. Use when generating reports, analyzing support performance, or reviewing KPIs.

- **Type:** Skill
- **Install:** `agentstack add skill-fazer-ai-chatwoot-skills-chatwoot-reporting-analytics`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [fazer-ai](https://agentstack.voostack.com/s/fazer-ai)
- **Installs:** 0
- **Category:** [Data & Analytics](https://agentstack.voostack.com/c/data-and-analytics)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [fazer-ai](https://github.com/fazer-ai)
- **Source:** https://github.com/fazer-ai/chatwoot-skills/tree/main/skills/chatwoot-reporting-analytics

## Install

```sh
agentstack add skill-fazer-ai-chatwoot-skills-chatwoot-reporting-analytics
```

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

## About

# Chatwoot Reporting & Analytics

Guide for using Chatwoot's reporting tools to analyze support performance.

## Report Types Overview

Chatwoot offers two generations of reporting APIs:

| API    | Tools                                                                                                          | Best for                                              |
| ------ | -------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------- |
| **V1** | `reports_account_overview`, `reports_account_summary`, `reports_agent_summary`, `reports_conversation_metrics` | Real-time overview, quick summaries                   |
| **V2** | `reports_v2_overview`, `reports_v2_agents`, `reports_v2_inboxes`, `reports_v2_teams`, `reports_v2_labels`      | Detailed breakdowns by dimension, date range analysis |

**Recommendation**: V2 endpoints are more comprehensive. Use V1 for real-time snapshots, V2 for historical analysis.

## Real-Time Overview

### Account overview (V1)

Get an instant snapshot of current conversation state:

```
reports_account_overview(account_id: 1)
```

Returns:

- Open conversations count
- Pending conversations count
- Unattended conversations count
- Agents online count

### Conversation meta counts

For conversation-status breakdowns:

```
conversations_meta(account_id: 1)
→ { open: 45, resolved: 1230, pending: 12, snoozed: 3, all: 1290, ... }
```

## V1 Reports

### Account summary

Summarized metrics for a date range:

```
reports_account_summary(
  account_id: 1,
  since: "2026-01-01",
  until: "2026-01-31",
  type: "account"
)
```

### Agent summary

Per-agent performance metrics:

```
reports_agent_summary(
  account_id: 1,
  since: "2026-01-01",
  until: "2026-01-31"
)
```

Returns per agent:

- Conversations handled
- Average first response time
- Average resolution time

### Conversation metrics

```
reports_conversation_metrics(
  account_id: 1,
  type: "account"
)
```

## V2 Reports (Recommended)

All V2 endpoints accept a consistent parameter set:

| Parameter    | Type    | Description                                         |
| ------------ | ------- | --------------------------------------------------- |
| `account_id` | integer | Required                                            |
| `since`      | string  | Start date (ISO format or Unix timestamp)           |
| `until`      | string  | End date                                            |
| `timezone`   | string  | IANA timezone (e.g., `"America/New_York"`, `"UTC"`) |

### V2 Overview

Aggregate metrics across the account:

```
reports_v2_overview(
  account_id: 1,
  since: "1704067200",
  until: "1706745600",
  timezone: "UTC"
)
```

### V2 Agent Report

Per-agent breakdown:

```
reports_v2_agents(
  account_id: 1,
  since: "1704067200",
  until: "1706745600",
  timezone: "America/New_York"
)
```

Returns per agent:

- `conversations_count` — Total conversations
- `avg_first_response_time` — Average first response (seconds)
- `avg_resolution_time` — Average time to resolve (seconds)
- `resolved_conversations_count` — Number resolved

### V2 Inbox Report

Per-inbox breakdown:

```
reports_v2_inboxes(
  account_id: 1,
  since: "1704067200",
  until: "1706745600",
  timezone: "UTC"
)
```

### V2 Team Report

Per-team breakdown:

```
reports_v2_teams(
  account_id: 1,
  since: "1704067200",
  until: "1706745600",
  timezone: "UTC"
)
```

### V2 Label Report

Per-label breakdown — useful for tracking issue categories:

```
reports_v2_labels(
  account_id: 1,
  since: "1704067200",
  until: "1706745600",
  timezone: "UTC"
)
```

## Key Metrics Explained

| Metric                       | Description                                          | Good benchmark       |
| ---------------------------- | ---------------------------------------------------- | -------------------- |
| **First Response Time**      | Time from conversation creation to first agent reply |  4.0 / 5.0          |
| **Unattended Conversations** | Open conversations with no agent response            | Should be 0          |
| **Agent Online**             | Agents currently available                           | Monitor for coverage |

## Date Handling

V2 reports accept dates as **Unix timestamps** (seconds since epoch):

```
# January 1, 2026 00:00:00 UTC → 1767225600
# January 31, 2026 23:59:59 UTC → 1767311999
```

Set `timezone` to match your team's working timezone for accurate daily breakdowns.

## Common Analysis Patterns

See `METRICS_REFERENCE.md` for detailed metric calculations.

See `EXAMPLES.md` for real-world reporting scenarios.

## Source & license

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

- **Author:** [fazer-ai](https://github.com/fazer-ai)
- **Source:** [fazer-ai/chatwoot-skills](https://github.com/fazer-ai/chatwoot-skills)
- **License:** MIT

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-fazer-ai-chatwoot-skills-chatwoot-reporting-analytics
- Seller: https://agentstack.voostack.com/s/fazer-ai
- Browse the marketplace: https://agentstack.voostack.com/browse

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