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Log Error Digest

CommunityPopular
zebbern
log-error-digest

Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or get distribution stats.

Overview

Publisherzebbern
Repositoryclaude-code-guide
Skill namelog-error-digest
Stars
4.6K
Forks
464
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zebbern on GitHub. Read the source before you install it.

Installation

Install the Log Error Digest AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zebbern/claude-code-guide.git /tmp/claude-code-guide
mkdir -p .claude/skills
cp -r /tmp/claude-code-guide/skills/log-error-digest .claude/skills/log-error-digest
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Log Error Digest in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Log Error Digest on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Log Error Digest is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Log Error Digest

Automated log file analysis that produces error clustering, frequency statistics, and time distribution reports.

Features

  • Error Clustering: Groups similar error messages by normalizing dynamic parts (IPs, UUIDs, numbers, etc.) to identify root causes
  • Frequency Statistics: Counts occurrences by error type, sorted by severity
  • Time Distribution: Shows error distribution by hour and by date, helping pinpoint peak error periods

Supported Log Formats

FormatDescriptionAuto-detection
JSONOne JSON object per line with timestamp/level/message fieldsStarts with {
syslogRFC 3164 format, e.g. Jan 1 12:00:00 host proc[pid]: msgStarts with month name
NginxAccess log or error log formatStarts with IP or date/path pattern

Usage

bash
python scripts/analyze_logs.py <log_file_path> [options]

Parameters

ParameterDescriptionDefault
log_filePath to the log file (required)-
--formatLog format: auto/json/syslog/nginxauto
--topShow Top N error clusters20
--outputExport results to a JSON fileTerminal output only
--levelFilter by log level (e.g. ERROR, WARN)All levels
--sinceOnly analyze logs after this time (ISO format)No limit
--untilOnly analyze logs before this time (ISO format)No limit

Examples

bash
# Auto-detect format and analyze the entire log file
python scripts/analyze_logs.py /var/log/app.log

# Specify Nginx format, show only Top 10 errors
python scripts/analyze_logs.py /var/log/nginx/error.log --format nginx --top 10

# Filter ERROR level only, export JSON report
python scripts/analyze_logs.py app.log --level ERROR --output report.json

# Analyze logs within a specific time range
python scripts/analyze_logs.py app.log --since 2024-01-01T00:00:00 --until 2024-01-02T00:00:00

Output

Terminal Output

=======================================================
              Log Analysis Report
=======================================================

📊 Overview
  Detected format: json
  Total lines:     15,234
  Parsed:          15,100 (parse failures: 134)
  Matched entries: 12,800
  Errors:          2,341
  Time range:      2024-01-01 00:03:12 ~ 2024-01-01 23:58:45

🔴 Top Error Clusters (47 total)
  #1   [×523  ] Connection refused to database at 10.0.1.5:5432
       First seen: 2024-01-01T00:15:30  Last seen: 2024-01-01T23:45:12
  #2   [×312  ] Timeout waiting for response from user-service after 30000ms
       First seen: 2024-01-01T02:10:00  Last seen: 2024-01-01T22:30:45
  #3   [×198  ] File not found: /data/uploads/img_99421.png
       First seen: 2024-01-01T08:00:00  Last seen: 2024-01-01T20:15:33
  ...

⏰ Time Distribution (by hour)
  00:00  █████░░░░░░░░░░░░░░░  42
  01:00  ██░░░░░░░░░░░░░░░░░░  18
  ...
  14:00  ████████████████████  523
  ...

📅 Time Distribution (by date)
  2024-01-01  ████████████████████  2,341

JSON Output

Use the --output parameter to export a structured JSON report for further processing or integration with monitoring systems.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Log Error Digest AI skill do?

Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or get distribution stats.

Why use Log Error Digest on TypingMind?

Because you install it once and use it with any model. Log Error Digest is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Log Error Digest in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zebbern/claude-code-guide/tree/main/skills/log-error-digest. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Log Error Digest?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Log Error Digest?

As many as you like. As long as a model supports skills, you can use Log Error Digest with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Log Error Digest AI skill free?

Yes. It is published on GitHub by zebbern under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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