profile — codesearch profile, veloria, PeterBooker, community, codesearch, ai agent skill, ide skills, agent automation, search, trigrams, wordpress, AI agent skills

v1.0.0
GitHub

About this Skill

Perfect for Go-focused AI Agents needing CPU and memory profiling capabilities. Run CPU and memory profiling with pprof to identify performance hotspots. Use when investigating high resource usage.

# Core Topics

PeterBooker PeterBooker
[9]
[1]
Updated: 3/11/2026

Quality Score

Top 5%
54
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
> npx killer-skills add PeterBooker/veloria/profile
Supports 19+ Platforms
Cursor
Windsurf
VS Code
Trae
Claude
OpenClaw
+12 more

Agent Capability Analysis

The profile skill by PeterBooker is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance. Optimized for codesearch, search, trigrams.

Ideal Agent Persona

Perfect for Go-focused AI Agents needing CPU and memory profiling capabilities.

Core Value

Empowers agents to identify CPU hotspots and memory allocators in Go code using pprof, facilitating optimized performance and resource utilization through regex-based code search and analysis of WordPress core versions, plugins, and themes.

Capabilities Granted for profile

Profiling CPU usage in Go packages
Analyzing memory allocation in WordPress plugins
Identifying performance bottlenecks in Go codebases

! Prerequisites & Limits

  • Requires Go codebase access
  • WordPress core, plugins, and themes only
  • pprof dependency
Project
SKILL.md
2.6 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8
SKILL.md
Readonly

CPU and Memory Profiling

Profile Go code to identify CPU hotspots and memory allocators using pprof.

Usage

  • /profile cpu ./internal/index/ - CPU profiling on index package
  • /profile memory ./internal/repo/ - Memory profiling on repo package
  • /profile all ./... - Both CPU and memory on all packages

Steps

  1. Parse arguments

    • First argument: Profile type (cpu, memory, or all)
    • Second argument: Package path (defaults to ./...)
  2. Create profile output directory

    bash
    1mkdir -p .profiles
  3. Run profiling benchmarks

    For CPU profiling:

    bash
    1go test -cpuprofile=.profiles/cpu.prof -bench=. $PACKAGE 2>&1

    For memory profiling:

    bash
    1go test -memprofile=.profiles/mem.prof -bench=. $PACKAGE 2>&1
  4. Analyze CPU profile

    bash
    1go tool pprof -top -cum .profiles/cpu.prof 2>&1 | head -30

    Identify:

    • Top 10 CPU consumers by cumulative time
    • Functions with high self time (computation hotspots)
    • Unexpected entries (potential optimization targets)
  5. Analyze memory profile

    bash
    1go tool pprof -top -alloc_space .profiles/mem.prof 2>&1 | head -30

    Identify:

    • Top allocators by total bytes
    • Functions with high allocation counts
    • Potential sources of GC pressure
  6. Generate flamegraph data (if requested)

    bash
    1go tool pprof -raw .profiles/cpu.prof > .profiles/cpu.raw
  7. Report findings

    Structure the report as:

    CPU Hotspots

    FunctionSelf%Cum%Observation

    Memory Allocators

    FunctionBytesAllocsObservation

    Optimization Suggestions

    • List specific, actionable recommendations
    • Reference line numbers where applicable
    • Note any patterns (e.g., repeated allocations in loops)

Interpreting Results

CPU Profile Indicators

  • High self%: Direct computation hotspot
  • High cum% but low self%: Calls expensive functions
  • runtime.*: GC or scheduler overhead

Memory Profile Indicators

  • High alloc_space: Total memory pressure
  • High alloc_objects: GC pressure from many small allocations
  • Repeated patterns: Loop allocations, string concatenation

Common Hotspots in Veloria

Watch for issues in:

  • (*Index).Search - Regex compilation, line reading
  • (*Repository).Load - Index file mapping
  • (*IndexedExtension).Update - Hot-swap operations
  • HTTP handlers - JSON marshaling, response writing

Cleanup

Profile files are stored in .profiles/. Add to .gitignore if not already present.

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is profile?

Perfect for Go-focused AI Agents needing CPU and memory profiling capabilities. Run CPU and memory profiling with pprof to identify performance hotspots. Use when investigating high resource usage.

How do I install profile?

Run the command: npx killer-skills add PeterBooker/veloria/profile. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for profile?

Key use cases include: Profiling CPU usage in Go packages, Analyzing memory allocation in WordPress plugins, Identifying performance bottlenecks in Go codebases.

Which IDEs are compatible with profile?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for profile?

Requires Go codebase access. WordPress core, plugins, and themes only. pprof dependency.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add PeterBooker/veloria/profile. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use profile immediately in the current project.

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