Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/curiositech/some_claude_skillsnpx agentmods add skills/curiositech/some_claude_skills/performance-profilingWrote 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/curiositech/some_claude_skills/performance-profiling)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/performance-profiling"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/performance-profiling.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00124 | $0.03985 |
| Opus 5 | $0.00062 | $0.01992 |
| Sonnet 5 | $0.00025 | $0.00797 |
| Haiku 4.5 | $0.00012 | $0.00398 |
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 4d 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 — 403 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Profiling
Find where your application actually spends time before touching a line of code. Covers the full stack: Node.js CPU and memory profiling, browser flame graphs, React render profiling, and database query analysis. The discipline here is profile first, optimize second — premature optimization is not a workflow, it is a guess.
When to Use
Use for:
- Diagnosing slow Node.js applications (CPU-bound, I/O-bound, memory pressure)
- Generating and reading flame graphs to find hot code paths
- Detecting memory leaks via heap snapshots and growth trends
- Profiling React component render performance with React Profiler
- Measuring browser rendering performance (Core Web Vitals, layout thrashing, long tasks)
- Database query profiling with EXPLAIN ANALYZE
- Measuring event loop utilization and latency
NOT for:
- Infrastructure monitoring, distributed tracing, or log aggregation (use
logging-observability) - Load testing and capacity planning (a separate domain)
- Network latency analysis between services (use distributed tracing tools)
- Database schema design optimization (separate from query profiling)
Core Decision: Where Is My App Slow?
flowchart TD
Start[App is slow. Where?] --> Layer{Which layer?}
Layer -->|Backend| Backend{What kind?}
Layer -->|Frontend/browser| Browser{What symptom?}
Layer -->|Unknown| Measure[Instrument first — add timing logs]
Backend -->|CPU pegged, slow responses| CPU[CPU Profiling]
Backend -->|Memory growing, crashes| Mem[Memory / Heap Profiling]
Backend -->|Fast CPU, slow I/O| IO{I/O type?}
IO -->|Database queries| DB[EXPLAIN ANALYZE + query profiler]
IO -->|Network calls| Network[Trace external calls, add timeouts]
IO -->|File system| FS[Check event loop utilization]
Browser -->|Slow initial load| Lighthouse[Lighthouse + bundle analysis]
Browser -->|Janky scrolling, animations| Rendering[Chrome Performance tab — layout thrashing]
Browser -->|Slow after interaction| React{React app?}
React -->|Yes| ReactProfiler[React Profiler + why-did-you-render]
React -->|No| JS[Chrome Performance — long tasks, main thread blocking]
CPU --> FlameGraph[Generate flame graph with 0x or clinic flame]
Mem --> HeapSnap[Take heap snapshots before/after suspected leak]
FS --> ELU[clinic bubbles — event loop utilization]
What ships with it
2 files 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.
- 4d ago First seen · 403 lines · 124 tokens per session scan A 302f595e0b38
performance-profiling is a skill published in the GitHub repository curiositech/some_claude_skills (214 stars, last pushed yesterday), licensed MIT. It adds 124 tokens to every session and 3,985 once invoked, about $0.0006 per session on Opus 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.
diagnose
Trace from a reproduced symptom to the source code that causes it. Pin the specific file and approximate line, rate confidence in the cause and clarity of the fix independently, and always propose a concrete fix.
repro-admin
Reproduce an EmDash admin UI bug. Attach a container, start the demo dev server, drive the admin with agent-browser using the dev-bypass session, and capture the reproduction as screenshots plus a replayable transcript.
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…
byted-util-volcengine-detect-retry
An orchestration workflow for Volcengine Cloud Detect, a service that checks websites or network endpoints from test locations.