Initial commit

.claude-plugin/plugin.json

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+{
+  "name": "application-profiler",
+  "description": "Profile application performance with CPU, memory, and execution time analysis",
+  "version": "1.0.0",
+  "author": {
+    "name": "Claude Code Plugins",
+    "email": "[email protected]"
+  },
+  "skills": [
+    "./skills"
+  ],
+  "commands": [
+    "./commands"
+  ]
+}

README.md

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+# application-profiler
+
+Profile application performance with CPU, memory, and execution time analysis

commands/profile.md

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+---
+description: Profile application performance metrics
+---
+
+# Application Profiler
+
+Analyze application performance including CPU usage, memory consumption, execution time, and identify bottlenecks.
+
+## Analysis Steps
+
+1. Identify the application technology stack (Node.js, Python, Java, etc.)
+2. Locate main application entry points and critical paths
+3. Analyze:
+   - CPU-intensive operations and hot paths
+   - Memory allocation patterns and potential leaks
+   - Synchronous vs asynchronous operations
+   - Database query patterns
+   - External API calls and network operations
+4. Generate profiling report with recommendations
+
+## Output Format
+
+Provide a markdown report with:
+- Executive summary of performance characteristics
+- CPU hotspots with file locations
+- Memory usage patterns
+- Execution time breakdown
+- Specific optimization recommendations
+- Code snippets showing issues and suggested fixes

plugin.lock.json

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+{
+  "$schema": "internal://schemas/plugin.lock.v1.json",
+  "pluginId": "gh:jeremylongshore/claude-code-plugins-plus:plugins/performance/application-profiler",
+  "normalized": {
+    "repo": null,
+    "ref": "refs/tags/v20251128.0",
+    "commit": "180bd05baefc498d3e04b552ffebf76f6e19e944",
+    "treeHash": "118ee27b7605c627ea67c1ea65de4d56a2124563b68ac467dff6de9cb0e14c33",
+    "generatedAt": "2025-11-28T10:18:09.927106Z",
+    "toolVersion": "publish_plugins.py@0.2.0"
+  },
+  "origin": {
+    "remote": "git@github.com:zhongweili/42plugin-data.git",
+    "branch": "master",
+    "commit": "aa1497ed0949fd50e99e70d6324a29c5b34f9390",
+    "repoRoot": "/Users/zhongweili/projects/openmind/42plugin-data"
+  },
+  "manifest": {
+    "name": "application-profiler",
+    "description": "Profile application performance with CPU, memory, and execution time analysis",
+    "version": "1.0.0"
+  },
+  "content": {
+    "files": [
+      {
+        "path": "README.md",
+        "sha256": "71abb11e4cf574bbfe42cc55f9332bf2cbf4a7cf313a570b558d68d6890642e8"
+      },
+      {
+        "path": ".claude-plugin/plugin.json",
+        "sha256": "9e64cdd7fae8c7e504f96ed015ff6f65d2a0e654d5e9bcae52d411310b782870"
+      },
+      {
+        "path": "commands/profile.md",
+        "sha256": "f175afe3802cf01e0b6d4a593035b7568b7470953fc9888ceb4fe2cf5b369413"
+      },
+      {
+        "path": "skills/application-profiler/SKILL.md",
+        "sha256": "0aec387e12a6cd5c7531fa9c3aa1e27c83957b0d7d988db1c9bf37bc72b6f688"
+      },
+      {
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+      },
+      {
+        "path": "skills/application-profiler/scripts/README.md",
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+      },
+      {
+        "path": "skills/application-profiler/assets/README.md",
+        "sha256": "37cf2ce2edc448840cccd639896aa30fd778b1d6821841dee3293452529b0a89"
+      }
+    ],
+    "dirSha256": "118ee27b7605c627ea67c1ea65de4d56a2124563b68ac467dff6de9cb0e14c33"
+  },
+  "security": {
+    "scannedAt": null,
+    "scannerVersion": null,
+    "flags": []
+  }
+}

skills/application-profiler/SKILL.md

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+---
+name: profiling-application-performance
+description: |
+  This skill enables Claude to profile application performance, analyzing CPU usage, memory consumption, and execution time. It is triggered when the user requests performance analysis, bottleneck identification, or optimization recommendations. The skill uses the application-profiler plugin to identify performance bottlenecks and suggest code-level optimizations. Use it when asked to "profile application", "analyze performance", or "find bottlenecks". It is also helpful when the user mentions specific performance metrics like "CPU usage", "memory leaks", or "execution time".
+allowed-tools: Read, Write, Edit, Grep, Glob, Bash
+version: 1.0.0
+---
+
+## Overview
+
+This skill empowers Claude to analyze application performance, pinpoint bottlenecks, and recommend optimizations. By leveraging the application-profiler plugin, it provides insights into CPU usage, memory allocation, and execution time, enabling targeted improvements.
+
+## How It Works
+
+1. **Identify Application Stack**: Determines the application's technology (e.g., Node.js, Python, Java).
+2. **Locate Entry Points**: Identifies main application entry points and critical execution paths.
+3. **Analyze Performance Metrics**: Examines CPU usage, memory allocation, and execution time to detect bottlenecks.
+4. **Generate Profile**: Compiles the analysis into a comprehensive performance profile, highlighting areas for optimization.
+
+## When to Use This Skill
+
+This skill activates when you need to:
+- Analyze application performance for bottlenecks.
+- Identify CPU-intensive operations and memory leaks.
+- Optimize application execution time.
+
+## Examples
+
+### Example 1: Identifying Memory Leaks
+
+User request: "Analyze my Node.js application for memory leaks."
+
+The skill will:
+1. Activate the application-profiler plugin.
+2. Analyze the application's memory allocation patterns.
+3. Generate a profile highlighting potential memory leaks.
+
+### Example 2: Optimizing CPU Usage
+
+User request: "Profile my Python script and find the most CPU-intensive functions."
+
+The skill will:
+1. Activate the application-profiler plugin.
+2. Analyze the script's CPU usage.
+3. Generate a profile identifying the functions consuming the most CPU time.
+
+## Best Practices
+
+- **Code Instrumentation**: Ensure the application code is instrumented for accurate profiling.
+- **Realistic Workloads**: Use realistic workloads during profiling to simulate real-world scenarios.
+- **Iterative Optimization**: Apply optimizations iteratively and re-profile to measure improvements.
+
+## Integration
+
+This skill can be used in conjunction with code editing plugins to implement the recommended optimizations directly within the application's source code. It can also integrate with monitoring tools to track performance improvements over time.

skills/application-profiler/assets/README.md

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+# Assets
+
+Bundled resources for application-profiler skill
+
+- [ ] report_template.md: Template for generating the performance report.
+- [ ] example_profiling_data.json: Example of profiling data that the tool can process.

skills/application-profiler/references/README.md

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+# References
+
+Bundled resources for application-profiler skill
+
+- [ ] profiling_tools_documentation.md: Documentation for the profiling tools used by the plugin.
+- [ ] performance_metrics_explained.md: Explanation of the performance metrics used in the analysis.
+- [ ] optimization_best_practices.md: Best practices for optimizing application performance.

skills/application-profiler/scripts/README.md

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+# Scripts
+
+Bundled resources for application-profiler skill
+
+- [ ] profile_application.py: Script to execute the profiling tools and collect performance data.
+- [ ] analyze_results.py: Script to analyze the collected performance data and identify bottlenecks.
+- [ ] generate_report.py: Script to generate a human-readable performance report.