optimize-simplicite-logs

# 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: ```sh 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 ```powershell /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 ```sh # 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.