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Optimize Simplicite Logs

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Efficiently parse and structure Simplicité log files.

by github37.7k stars on github/awesome-copilot
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Updated Aug 10, 2026
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Free · Opens the source repo

What Optimize Simplicite Logs does

The Optimize Simplicite Logs skill enables developers and data analysts to effectively parse raw Simplicité log files in .txt format. By utilizing either the provided Python or PowerShell scripts, users can filter out unnecessary log data, resulting in structured JSON output that is significantly more manageable. This capability is particularly important when dealing with large log files, as it helps to optimize the context size for AI applications, potentially saving around 56% of tokens during processing.

The skill is designed to extract relevant fields such as timestamp, level, and body from verbose logs, while discarding irrelevant structural information. This ensures that the output is not only smaller but also more focused, making it easier to troubleshoot issues. The multi-line support feature captures stack traces and multiline errors effectively, which are often overlooked in standard text searches. Users can also choose to print the JSON output directly to the console, facilitating seamless integration with other tools in their workflow.

This skill is ideal for developers and data professionals who regularly work with Simplicité applications and need to analyze log data efficiently. It streamlines the process of log analysis by providing a straightforward way to convert and filter logs, allowing users to focus on the most pertinent information without being overwhelmed by noise. Whether you are troubleshooting an issue or conducting a performance analysis, this skill provides the necessary tools to work with Simplicité logs effectively.

When to use it

Use this skill when you need to analyze Simplicité log files and want to avoid the overhead of processing large raw text files.

When not to use it

This skill may not be suitable if your log format deviates significantly from the standard Simplicité output, as parsing may fail or be less effective.

What you can build with it

Log Analysis for Troubleshooting

Use the skill to convert large Simplicité logs into JSON format, focusing on key fields for quick troubleshooting.

Data Optimization for AI Processing

Reduce token usage in AI models by filtering and structuring log data, making it easier to manage context.

Integrating with Other Tools

Pipe the JSON output directly to other command-line tools for further processing or analysis.

How to install Optimize Simplicite Logs

View source

1. Install with the skills CLI

npx skills add github/awesome-copilot/optimize-simplicite-logs --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by github

Optimize Simplicite Logs

This skill provides the capability to parse Simplicité logs from a raw .txt file, filter fields to reduce noise, and output the result as structured JSON. This is critical for optimizing AI context size (saving ~56% of tokens) and providing structured, predictable data for troubleshooting.

When to Use This Skill

Use this skill when you need to:

  • Analyze user-provided Simplicité log files in .txt format.
  • Avoid ingesting massive raw log files into your context window.
  • Extract structured fields (like timestamp, level, body) from verbose multi-line log output.

IMPORTANT: Instead of directly reading a raw .txt log file provided by the user using file read tools, you must use one of the log converter scripts (PowerShell or Python) to parse the file into a JSON format first, optionally extracting only the fields needed.

Prerequisites

  • Access to either the PowerShell script (/scripts/SimpliciteLog2Json.ps1) or the Python script (/scripts/simplicite-log2json.py).

Core Capabilities

1. Context Optimization

Reduces the tokens consumed by large Simplicité logs by extracting only relevant log fields (e.g. body, timestamp, level) and discarding non-relevant structural log data (like app, endpoint, contextPath).

2. Multi-line Support

Properly captures stack traces and multiline errors inside the body field of the JSON structure, which a simple text search might miss.

3. Stdout Support

If no output path is provided for the JSON file (e.g. omitting --output or -Output), the parsed JSON will be printed directly to stdout, allowing you to pipe the output to other tools.

Output Summary

After processing, the tool prints a summary to stderr (or console):

Processed: 123 entries, Skipped: 2 entries

Usage Examples

Example 1: Python Version (Recommended)

Convert a log file to JSON, keeping only the most important fields:

python /absolute/path/to/skills/optimize-simplicite-logs/scripts/simplicite-log2json.py <input.txt> --include timestamp,level,body --output <output.json>

Example 2: PowerShell Version

/python /absolute/path/to/skills/optimize-simplicite-logs/scripts/SimpliciteLog2Json.ps1 -InputPath "<input.txt>" -Output "<output.json>" -Include "body,timestamp,level"

After generating the <output.json>, you can safely read the resulting file to perform your analysis.

Guidelines

  1. Always Convert First: Never directly read .txt log files from Simplicité using standard text reading tools. Always convert them to JSON using the available scripts.
  2. Filter Fields: Use --include (Python) or -Include (PowerShell) to restrict fields to what is absolutely necessary to diagnose the issue (usually timestamp,level,body).
  3. Available Fields: The fields you can filter include: timestamp, app, level, endpoint, contextPath, event, user, class, function, rowId, body.

Common Patterns

Pattern: Fast Contextual Troubleshooting

# 1. Run the script to generate a minified JSON output in the current directory
python /absolute/path/to/skills/optimize-simplicite-logs/scripts/simplicite-log2json.py logs.txt --include timestamp,level,body --output logs_minified.json

# 2. Then read logs_minified.json to understand the context.

Limitations

  • The parser depends on a fixed regex pattern that matches the standard Simplicité log output. If the log format has been heavily customized, parsing might fail or degrade.

Frequently asked questions about Optimize Simplicite Logs

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