github/awesome-copilot/optimize-simplicite-logs
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capability to parse Simplicité logs from a raw `.txt` file, filter fields to reduce noise, and output the result as structured JSON.
Install
npx vskill@latest install github/awesome-copilot/optimize-simplicite-logsSKILL.md
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.
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
- 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
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.
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/optimize-simplicite-logs/SKILL.md
Popularity
- Repository stars
- 34,485
- Repository forks
- 4,221
- 7-day trend score
- 52
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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