Borrowing it
Nothing to install: this file belongs to Stankye/profiler-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Stankye/profiler-mcp/main/.claude/skills/profile-hotspots/SKILL.mdgit clone --depth 1 https://github.com/Stankye/profiler-mcpWrote 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/stankye/profiler-mcp/profile-hotspots)<a href="https://agentmods.dev/skills/stankye/profiler-mcp/profile-hotspots"><img src="https://agentmods.dev/badge/skills/stankye/profiler-mcp/profile-hotspots/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/stankye/profiler-mcp/profile-hotspots"><img src="https://agentmods.dev/badge/skills/stankye/profiler-mcp/profile-hotspots.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 | $0.00042 | $0.00653 |
| Opus 5 | $0.00021 | $0.00327 |
| Sonnet 5 | $0.00008 | $0.00131 |
| Haiku 4.5 | $0.00004 | $0.00065 |
Grade A, and why
profile-hotspots 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 10d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Profile hotspots
Choosing a server
- Call
vtune_checkanduprof_checkfirst. They tell you which profiler is actually available, in which mode (real,mock,unavailable), and any platform caveats. - On Intel CPUs prefer vtune; on AMD CPUs prefer uprof (VTune's hw sampling and uProf's
PMC/IBS configs each need their own vendor's silicon). On Intel, uProf only supports
tbp(timer) collection. Either server inmockmode is fine for testing workflows — but never present mock numbers as real measurements; every result is stamped with its mode.
Collecting
vtune_collect(analysis="hotspots", command=["/abs/path/app", "arg"], ...)oruprof_collect(config="hotspots", command=[...]). Use absolute paths for the target.- Attach to a running process with
pid=instead ofcommand=— thenduration_secis required. - Keep first runs short and representative (workloads with a
--seconds Nstyle knob are ideal). Both tools return aresult_id— everything downstream takes that id. - If collection fails, the error text usually names the fix (missing binary, permissions:
perf_event_paranoid, driver). Re-run*_checkafter changing the environment.
Reading results
- Start with
*_report_summary(result_id)— elapsed vs CPU time tells you the parallelism story before any function ranking. *_report_hotspots(result_id, top_n=10)gives normalized rows{function, module, metric, value, percent}. A healthy profile concentrates time in few functions; a flat profile (many ~2% rows) means the workload or inlining needs attention, not micro-optimization.- Drill down only when needed via
vtune_report_raw(other report types:top-down,callstacks,hw-events) oruprof_report_raw— output is byte-capped; narrow with filters instead of paging through everything.
Interpreting
-
30% in one leaf function → optimize that function (algorithm first, then code).
- High CPU time in runtime libs (
libgomp,libpthread) → synchronization/imbalance; switch to a threading-oriented analysis (vtune_collect(analysis="threading")). - Memory-bound suspicion (high time, low IPC) →
analysis="memory-access"(VTune, needs uncore access) orconfig="memory"/"ibs"(uProf, needs AMD hw). - Record the
result_idof any baseline you may want to compare against later; the optimize-loop skill builds on*_compare.
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.
- 10d ago First seen · 50 lines · 42 tokens per session scan A 2e2a673a5019
profile-hotspots is a skill published in the GitHub repository Stankye/profiler-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 653 once invoked, about $0.0002 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 2026-08-31.
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