Web Profiler Bundle for Openclaw

A local-first profiling toolkit for tracking HTTP request timings, memory usage, and database query performance via the command line.

bytesagain1
v1.0.0
Mar 20, 2026
0
802
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install web-profiler-bundle

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install web-profiler-bundle using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Web Profiler Bundle?

Web Profiler Bundle is a comprehensive utility designed for developers who need deep visibility into their application performance without the overhead of external SaaS platforms. As a featured addition to the Openclaw Skills ecosystem, it provides a robust set of commands to log, analyze, and compare profiling data locally, ensuring your performance metrics remain private and easily accessible.

The tool focuses on providing high-fidelity breakdowns of request lifecycles, including middleware overhead and N+1 query detection. By integrating seamlessly into your existing developer workflow, it allows for rapid debugging of slow routes and optimization of resource-heavy endpoints using standard Unix utilities and a Python-based runtime.

Web Profiler Bundle Use Cases

  • Debugging slow HTTP routes: Log profiling runs with precise timing data to identify performance bottlenecks over time.
  • Analyzing query performance: Record database query breakdowns to detect and eliminate N+1 issues.
  • Inspecting middleware execution: Measure the specific latency and memory consumption introduced by each layer of your middleware stack.
  • CI/CD Performance Reporting: Export accumulated data to JSON or CSV for automated performance regressions in your build pipelines.
  • Optimization Benchmarking: Use side-by-side comparisons to validate the impact of code changes on response times.

How Web Profiler Bundle Works

  1. Execution: You trigger a profiling task using the run or check commands, passing in the relevant performance metrics.
  2. Local Logging: The tool appends the data to specific log files located in your local share directory with high-resolution timestamps.
  3. Aggregation: A unified history log tracks every operation across different command types for a complete audit trail.
  4. Analysis: Use the analyze or compare commands to process the logged data and identify trends or regressions.
  5. Reporting: Generate human-readable reports or machine-parseable exports (JSON/CSV) for further visualization or sharing with your team.

Web Profiler Bundle Setup

To get started with this component of your Openclaw Skills library, ensure you have Python 3 and Bash 4.0+ installed.

# The bundle automatically initializes its data directory on first run
web-profiler-bundle help

# Run your first profiling log
web-profiler-bundle run "GET /api/v1/users - 200ms, 12MB"

Web Profiler Bundle Data Schema & Taxonomy

All data is managed locally to ensure privacy and speed. The schema follows a consistent timestamped format:

File Description
run.log Primary logs for HTTP request profiling sessions.
analyze.log Records of query breakdowns and memory analysis.
history.log A master record of every command executed via the bundle.
config.log History of configuration changes and environment settings.

Format: YYYY-MM-DD HH:MM|value

Web Profiler Bundle Advanced Features

  • Multi-format Exports: Native support for JSON, CSV, and TXT for easy integration with external data tools.
  • Keyword Search: Global search functionality across all local logs to find specific memory leaks or slow endpoints.
  • Batch Processing: Ability to handle multiple profiling operations in a single session for complex service architectures.
  • Comparative Analysis: Built-in logic to compare 'warm' vs 'cold' cache states or 'before' vs 'after' optimization results.

SKILL.md


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