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Skillsgithub/awesome-copilotoptimize-simplicite-logs

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.

npx skills add https://github.com/github/awesome-copilot --skill optimize-simplicite-logs
SKILL.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 .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.
Installs0
GitHub Stars34.5k
LanguagePython
AddedJun 5, 2026
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