Agent skill · data analytics · github
optimize-simplicite-logs
capability to parse Simplicité logs from a raw `.txt` file, filter fields to reduce noise, and output the result as structured JSON.
Why this skill is useful
Adds a Python and PowerShell script for parsing and structuring Simplicité logs into JSON, which the AI wouldn't generate on its own.
What it needs
Requires powershell, python installed locally. About 2k tokens when loaded. Last updated 2026-08-07. 37,534 stars on the source repository.
What this skill does
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): Usage Examples Example 1: Python Version (Recommended) Convert a log file to JSON, keeping only the most important fields: Example 2: PowerShell Version After generating the <output.json>, you can safely read the resulting file to perform your analysis. Guidelines 1. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills github/optimize-simplicite-logs