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 ArabelaTso/Skills-4-SE --skill interval-profiling-performance-analyzergit clone --depth 1 https://github.com/ArabelaTso/Skills-4-SEWrote 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/arabelatso/skills-4-se/interval-profiling-performance-analyzer)<a href="https://agentmods.dev/skills/arabelatso/skills-4-se/interval-profiling-performance-analyzer"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/interval-profiling-performance-analyzer/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/arabelatso/skills-4-se/interval-profiling-performance-analyzer"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/interval-profiling-performance-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Privilege Escalation · line 176 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
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 | $0.00116 | $0.01480 |
| Opus 5 | $0.00058 | $0.00740 |
| Sonnet 5 | $0.00023 | $0.00296 |
| Haiku 4.5 | $0.00012 | $0.00148 |
Grade B, and why
interval-profiling-performance-analyzer scanned grade B with 1 finding 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 9d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo apt-get install linux-tools-generic How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interval Profiling & Performance Analyzer
Profile programs to identify performance bottlenecks and generate optimization recommendations with visualizations.
Workflow
1. Understand Requirements
Clarify the profiling task:
- Target program: Which file/executable to profile?
- Language: Python, Java, or C/C++?
- Test scenarios: What workload or test cases to run?
- Focus area: CPU time, memory usage, or both?
2. Select Profiling Tool
Choose based on language and environment:
Python:
- Use
scripts/profile_python.py(cProfile + tracemalloc) - Captures function-level timing and memory usage
- No code modification required
Java:
- Use
scripts/profile_java.py(Java Flight Recorder) - Requires JDK 11+ with JFR support
- Low overhead, production-safe
C/C++:
- Use
scripts/profile_cpp.py(perf or gprof) perf: Linux only, no recompilation neededgprof: Cross-platform, requires-pgcompilation flag
For detailed tool information, see references/profiling-tools.md.
3. Run Profiling
Execute the appropriate profiling script:
Python example:
python scripts/profile_python.py target_script.py
Java example:
python scripts/profile_java.py MainClass ./bin 30
# Arguments: MainClass, classpath, duration_seconds
C/C++ example:
python scripts/profile_cpp.py ./program --tool perf
# Or use gprof (requires compilation with -pg):
python scripts/profile_cpp.py ./program --tool gprof
All scripts generate profile_results.json containing:
- intervals: All profiled functions with metrics
- hotspots: Functions exceeding 5% of execution time
- recommendations: Actionable optimization suggestions
- summary: Overall statistics
4. Generate Visualizations
Create interactive HTML report and flame graph data:
python scripts/generate_visualization.py profile_results.json profile_report.html
Outputs:
profile_report.html: Interactive report with charts and recommendationsflamegraph.txt: Data for flame graph generation (use flamegraph.pl if available)
What ships with it
7 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.
- 9d ago First seen · 197 lines · 116 tokens per session scan B ad52dc3c05d3
interval-profiling-performance-analyzer is a skill published in the GitHub repository ArabelaTso/Skills-4-SE (252 stars, last pushed 22d ago), licensed Apache-2.0. It adds 116 tokens to every session and 1,480 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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