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 VersoXBT/claude-initial-setup --skill profiling-guidegit clone --depth 1 https://github.com/VersoXBT/claude-initial-setupWrote 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/versoxbt/claude-initial-setup/profiling-guide)<a href="https://agentmods.dev/skills/versoxbt/claude-initial-setup/profiling-guide"><img src="https://agentmods.dev/badge/skills/versoxbt/claude-initial-setup/profiling-guide/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/versoxbt/claude-initial-setup/profiling-guide"><img src="https://agentmods.dev/badge/skills/versoxbt/claude-initial-setup/profiling-guide.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 | $0.00070 | $0.01830 |
| Opus 5.5 | $0.00028 | $0.00732 |
| Sonnet 5.5 | $0.00014 | $0.00366 |
| Haiku 4.5 | $0.00007 | $0.00183 |
Grade A, and why
profiling-guide 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 — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Profiling Guide
Measure before optimizing. Use profiling tools to identify actual bottlenecks instead of guessing. This guide covers profiling for JavaScript/Node.js, Python, and Go.
When to Use
- Application or endpoint is slow and you need to find the bottleneck
- Investigating memory leaks or growing memory usage
- Optimizing hot paths in CPU-intensive code
- Generating flame graphs for visual performance analysis
- Comparing performance before and after a change
Core Patterns
Chrome DevTools Profiling (Frontend)
Profile rendering, JavaScript execution, and memory in the browser.
## Performance Tab Workflow
1. Open DevTools (Cmd+Option+I / F12)
2. Go to Performance tab
3. Click Record, perform the slow action, click Stop
4. Analyze the flame chart:
- Yellow = JavaScript execution
- Purple = Rendering/layout
- Green = Painting
- Look for long tasks (>50ms, marked with red triangle)
## Key Metrics
- First Contentful Paint (FCP): < 1.8s
- Largest Contentful Paint (LCP): < 2.5s
- Total Blocking Time (TBT): < 200ms
- Cumulative Layout Shift (CLS): < 0.1
## Memory Tab Workflow
1. Go to Memory tab
2. Take Heap Snapshot
3. Perform suspected leaking action
4. Take another Heap Snapshot
5. Compare snapshots (select "Comparison" view)
6. Sort by "Delta" to find growing object counts
Programmatic performance measurement:
// Measure specific operations
performance.mark('fetch-start');
const data = await fetchLargeDataset();
performance.mark('fetch-end');
performance.measure('data-fetch', 'fetch-start', 'fetch-end');
const measure = performance.getEntriesByName('data-fetch')[0];
// measure.duration gives you milliseconds
// React component profiling
import { Profiler } from 'react';
function onRenderCallback(
id: string,
phase: 'mount' | 'update',
actualDuration: number,
) {
if (actualDuration > 16) { // Longer than one frame at 60fps
console.warn(`Slow render: ${id} took ${actualDuration.toFixed(2)}ms`);
}
}
<Profiler id="UserList" onRender={onRenderCallback}>
<UserList users={users} />
</Profiler>
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 · 250 lines · 70 tokens per session scan A 1a9f63920f41
profiling-guide is a skill published in the GitHub repository VersoXBT/claude-initial-setup (4 stars, last pushed 5mo ago), licensed MIT. It adds 70 tokens to every session and 1,830 once invoked, about $0.0003 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
learner
Post-debugging knowledge extraction — captures non-obvious, codebase-specific learnings that pass quality gates. Invoke after resolving tricky bugs or discovering surprising behavior.
git-advanced-workflows
Master advanced Git workflows including rebasing, cherry-picking, bisect, worktrees, and reflog to maintain clean history and recover from any situation. Use when managing complex Git histories, collaborating on feature branches, or troubleshooting repository issues.
principle-attack-the-premise
Apply when two or more fixes that share one premise have failed the same gate. Write the premise down and test it directly before you write another fix that assumes it.
vigil-instrument
Instrument a service with OpenTelemetry — RED metrics, structured logs, distributed tracing, and health checks. Outputs actual code and config, not a plan. Use when asked to "add monitoring", "instrument this", "add logging", "set up tracing", or "observability".
forge-diagnose
Diagnose runtime infrastructure issues — cold starts, timeouts, scaling problems, network failures. Use when asked about "infra is slow", "cold starts", "network issues", "why is this timing out", "scaling problem", "latency spikes", or "service is down".
decision-table
Use when the user wants a code-grounded decision table for current behavior, wants to compare current behavior against a plan or work item, or needs a control-flow artifact for recovery, retry, finalization, validation, state-machine, or review-heavy edge cases.