Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Claude-Code-Community-Ireland/claude-code-resources --skill performance-profilinggit clone --depth 1 https://github.com/Claude-Code-Community-Ireland/claude-code-resourcesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/claude-code-community-ireland/claude-code-resources/performance-profiling)<a href="https://agentmods.dev/skills/claude-code-community-ireland/claude-code-resources/performance-profiling"><img src="https://agentmods.dev/badge/skills/claude-code-community-ireland/claude-code-resources/performance-profiling/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/claude-code-community-ireland/claude-code-resources/performance-profiling"><img src="https://agentmods.dev/badge/skills/claude-code-community-ireland/claude-code-resources/performance-profiling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.03189 |
| Opus 5.5 | $0.00012 | $0.01276 |
| Sonnet 5.5 | $0.00006 | $0.00638 |
| Haiku 4.5 | $0.00003 | $0.00319 |
Grade A, and why
performance-profiling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Profiling
Core Principle: Measure First
Never optimize without data. Gut-feeling optimization leads to wasted effort on non-bottlenecks. Always follow this sequence:
- Define a measurable performance goal (e.g., "page load under 2 seconds on 3G").
- Measure current performance with appropriate tooling.
- Identify the actual bottleneck from profiling data.
- Apply a targeted fix.
- Re-measure to confirm improvement.
- Repeat until the goal is met.
Bottleneck Categories
Before diving into tools, classify the bottleneck you are investigating:
| Category | Symptoms | Key Metrics | Common Causes |
|---|---|---|---|
| CPU | High CPU usage, slow computation | CPU time, flame graph hot paths | Tight loops, unoptimized algorithms, excessive parsing |
| Memory | Growing memory footprint, OOM errors | Heap size, allocation rate, GC pauses | Memory leaks, large object graphs, unbounded caches |
| I/O (Disk) | Slow reads/writes, high iowait | IOPS, throughput, latency | Synchronous file ops, missing buffering, excessive logging |
| Network | High latency, timeouts | RTT, TTFB, bandwidth utilization | Chatty APIs, missing compression, no connection reuse |
| Database | Slow queries, connection exhaustion | Query time, lock contention, pool usage | Missing indexes, N+1 queries, full table scans |
Browser Performance Profiling
Chrome DevTools Performance Tab
Use the Performance tab to capture a runtime profile:
- Open DevTools (
Cmd+Option+I/Ctrl+Shift+I). - Go to the Performance tab.
- Click Record, perform the user action, then Stop.
- Analyze the flame chart for long tasks (anything over 50ms blocks the main thread).
- Check the Summary pane for a breakdown of Scripting, Rendering, Painting, and Idle time.
Key things to look for:
- Long Tasks (red corners in the timeline) blocking user interaction.
- Layout thrashing — repeated forced reflows from interleaved reads and writes.
- Excessive paint regions — use the Rendering drawer to enable Paint Flashing.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 376 lines · 31 tokens per session scan A d281edf6fc59
performance-profiling is a skill published in the GitHub repository Claude-Code-Community-Ireland/claude-code-resources (11 stars, last pushed 4mo ago), licensed MIT. It adds 31 tokens to every session and 3,189 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
debug-optimize-lcp
Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…
systematic-debugging
Use when debugging a failing test, build error, or runtime issue that isn't immediately obvious. Guides a 4-phase root cause analysis instead of random fix attempts.
log-error-digest
Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…
deck-retro
Run a fully local agent-deck retrospective over the user's own transcripts, Recall index and logs. Use when a user wants to find recurring failures or take their own finding from investigation through synthetic reproduction, a user-filed issue, a test-first fix and contributor PR handoff. Also use for weekly usage…
incident-response-incident-response
Coordinate production incident triage, mitigation, investigation, recovery, and follow-up. Use when responding to outages or other incidents that require structured operational coordination.
cwv-optimizer
Diagnose and fix Core Web Vitals issues on AEM Edge Delivery Services pages. Goes deeper than generic CWV advice by understanding EDS-specific performance patterns including the 100KB LCP budget, E-L-D loading phases, block rendering behavior, and third-party script impact. Produces specific fixes for LCP, CLS, and…