
optimize-simplicite-logs
✓ Official★ 36,202by github · part of github/awesome-copilot
capability to parse Simplicité logs from a raw `.txt` file, filter fields to reduce noise, and output the result as structured JSON.
This is the playbook your agent receives when the skill activates — you don't need to read it to use the skill, but it's here to audit before installing.
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
.txtformat. - 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.
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 entriesGuidelines
- Always Convert First: Never directly read
.txtlog files from Simplicité using standard text reading tools. Always convert them to JSON using the available scripts. - Filter Fields: Use
--include(Python) or-Include(PowerShell) to restrict fields to what is absolutely necessary to diagnose the issue (usuallytimestamp,level,body). - 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.npx skills add https://github.com/github/awesome-copilot --skill optimize-simplicite-logsRun this in your project — your agent picks the skill up automatically.
Prerequisites
- Access to either the PowerShell script (
/scripts/SimpliciteLog2Json.ps1) or the Python script (/scripts/simplicite-log2json.py).
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.
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.
Licensed under MIT— you can use, modify, and redistribute it under that license's terms.
View the full license file on GitHub →