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.
- License 许可
- MIT
- 最近更新
- 2026-11-13
- Stars
- ★ 4.1w
- Forks
- 5.3k
01 前言 Front Matter
- name
- optimize-simplicite-logs
- description
- capability to parse Simplicité logs from a raw `.txt` file, filter fields to reduce noise, and output the result as structured JSON.
02 资源文件 3
- 脚本scripts/simplicite-log2json.py4.4 KB
- 脚本scripts/SimpliciteLog2Json.ps14.2 KB
- 其他SKILL.md.tmpl23.1 KB
03 SKILL.md 正文
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):
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
- 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.
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.
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