capability to parse Simplicité logs from a raw `.txt` file, filter fields to reduce noise, and output the result as structured JSON.
f11a4e4This 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.
Use this skill when you need to:
.txt format.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.
/scripts/SimpliciteLog2Json.ps1) or the Python script (/scripts/simplicite-log2json.py).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).
Properly captures stack traces and multiline errors inside the body field of the JSON structure, which a simple text search might miss.
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.
After processing, the tool prints a summary to stderr (or console):
Processed: 123 entries, Skipped: 2 entries
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>
/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.
.txt log files from Simplicité using standard text reading tools. Always convert them to JSON using the available scripts.--include (Python) or -Include (PowerShell) to restrict fields to what is absolutely necessary to diagnose the issue (usually timestamp,level,body).timestamp, app, level, endpoint, contextPath, event, user, class, function, rowId, body.# 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.
Copy a source-pinned command for your client. You run it yourself.
Destination: .claude/skills/optimize-simplicite-logs · pinned to the source commit
# Run from your project root
git clone https://github.com/github/awesome-copilot.git .skillboard-tmp
git -C .skillboard-tmp checkout f11a4e441c5ff061b4f8ae37952be8c602e4034e
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/skills/optimize-simplicite-logs" ".claude/skills/"
rm -rf .skillboard-tmpReview the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.
sudo apt update && sudo apt install -y gitnpm install -g @anthropic-ai/claude-code# Run from your project root
git clone https://github.com/github/awesome-copilot.git .skillboard-tmp
git -C .skillboard-tmp checkout f11a4e441c5ff061b4f8ae37952be8c602e4034e
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/skills/optimize-simplicite-logs" ".claude/skills/"
rm -rf .skillboard-tmpDestination: .claude/skills/optimize-simplicite-logs
Scanner static-checks@0.1.0 · commit f11a4e441c5f. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.
No static rules matched. This is not a safety guarantee.