Optimize-Simplicite-Logs
Optimize-Simplicite-Logs是一款code方向的AI技能,核心价值是capability to parse Simplicité logs from a raw `,可用于解决开发者在code领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
capability to parse Simplicité logs from a raw `.txt` file, filter fields to reduce noise, and output the result as structured JSON.
mkdir -p ./skills/optimize-simplicite-logs && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/optimize-simplicite-logs/SKILL.md -o ./skills/optimize-simplicite-logs/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# 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 entriesUsage 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.
🎯 Best For
- Claude users
- GitHub Copilot users
- Software engineers
- Development teams
- Tech leads
💡 Use Cases
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Optimize-Simplicite-Logs to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Is Optimize-Simplicite-Logs compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Optimize-Simplicite-Logs?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Optimize-Simplicite-Logs?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/optimize-simplicite-logs/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.