# fraudlens

> fraudlens — cognis-digital-fraudlens. Use this tool when you need to detect and analyze fraudulent transactions in a data stream, leveraging customizable rules and machine learning models to optimize precision and recall. It solves problems related to financial security and risk management by identifying potential threats and evaluating the effectiveness of fraud detection strategies. The tool takes in a stream of transactions and outputs key metrics, including precision, recall, and alert volume, via the terminal interface.

Canonical page: https://skillsregistry.net/skills/cognis-digital-fraudlens  
JSON: https://api.skillsregistry.net/v1/skills/cognis-digital-fraudlens

## Description

Replays a stream of transactions against pluggable fraud rules and ML scorers, emitting precision/recall and alert volume from the terminal.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/cognis-digital/fraudlens)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "cognis-digital-fraudlens"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cognis-digital-fraudlens` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cognis-digital-fraudlens/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt