# Log Analyzer

> Use this tool when you need to efficiently analyze log files and troubleshoot issues. The Log Analyzer solves problems related to log file analysis, such as error identification and event correlation, by accepting log files as input and providing insights and patterns as output. It is particularly useful when working with large log files or multiple file types, and supports natural language queries and sensitive data detection.

Canonical page: https://skillsregistry.net/skills/fato07-log-analyzer  
JSON: https://api.skillsregistry.net/v1/skills/fato07-log-analyzer

## Description

Enables Claude to directly read and analyze log files without copy-pasting. Provides automatic format detection across 9+ common log types, pattern searching with context, error extraction and grouping with stack trace capture, natural language queries about logs, sensitive data detection (PII, credentials), event correlation across multiple files, and streaming support for large files (1GB+).

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/fato07-log-analyzer)
- **Repository:** <https://github.com/fato07/log-analyzer-mcp>

## 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": "fato07-log-analyzer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/fato07-log-analyzer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/fato07-log-analyzer/pull`

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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