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 phuonghx/aim-cli --skill performance-profilinggit clone --depth 1 https://github.com/phuonghx/aim-cliWrote 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/phuonghx/aim-cli/performance-profiling)<a href="https://agentmods.dev/skills/phuonghx/aim-cli/performance-profiling"><img src="https://agentmods.dev/badge/skills/phuonghx/aim-cli/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/phuonghx/aim-cli/performance-profiling"><img src="https://agentmods.dev/badge/skills/phuonghx/aim-cli/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 | $0.00076 | $0.00875 |
| Opus 5.5 | $0.00030 | $0.00350 |
| Sonnet 5.5 | $0.00015 | $0.00175 |
| Haiku 4.5 | $0.00008 | $0.00088 |
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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Profiling
Measure, then analyze, then change -- in that order. Optimizing on a hunch wastes effort.
Automation
| Script | What it does | How to run |
|---|---|---|
scripts/lighthouse_audit.py |
Runs a Lighthouse audit and extracts scores | python scripts/lighthouse_audit.py https://example.com |
Core Web Vitals
What "good" looks like
| Metric | Good | Poor | What it captures |
|---|---|---|---|
| LCP | under 2.5s | over 4.0s | How fast the main content paints |
| INP | under 200ms | over 500ms | How responsive interactions feel |
| CLS | under 0.1 | over 0.25 | How much the layout jumps around |
Where to measure each stage
- While developing -- local Lighthouse runs.
- In CI -- Lighthouse CI to catch regressions before merge.
- In production -- real-user monitoring (RUM), because lab numbers miss field reality.
The profiling loop
- Baseline -- record where things stand today.
- Isolate -- find the single biggest bottleneck.
- Fix -- make one focused change aimed at it.
- Verify -- re-measure and confirm the change actually helped.
Matching the tool to the problem
- Whole-page load -> Lighthouse
- Shipping too much JavaScript -> a bundle analyzer
- Sluggish runtime behavior -> the Performance panel in DevTools
- Climbing memory -> the Memory panel
- Slow requests -> the Network panel
Reading the bundle
Red flags
- A heavy dependency sitting near the top of the bundle.
- The same code duplicated across multiple chunks.
- Large stretches of code the page never executes (low coverage).
- One giant chunk with no splitting.
Corresponding moves
- Heavy library -> import only the pieces you use.
- Duplicate dependency -> dedupe and align versions.
- Route bundled into the entry point -> split it out.
- Dead exports -> rely on tree-shaking, or delete them.
Runtime and memory
Performance panel cues
- Long tasks over ~50ms block the main thread and hurt responsiveness.
- A flood of tiny tasks often means work that could be batched.
- Heavy layout/paint activity points at a rendering bottleneck.
- Big script blocks point at expensive JavaScript.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 113 lines · 76 tokens per session scan A b7cf9b8deb23
performance-profiling is a skill published in the GitHub repository phuonghx/aim-cli (1 stars, last pushed 3mo ago), licensed MIT. It adds 76 tokens to every session and 875 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 2026-08-31.
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