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 agentmods add skills/jabrena/cursor-rules-examples/162-java-profiling-analyzenpx skills add jabrena/cursor-rules-examples --skill 162-java-profiling-analyzegit clone --depth 1 https://github.com/jabrena/cursor-rules-examplesWhat 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 | $0.00075 | $0.00516 |
| Opus 5 | $0.00037 | $0.00258 |
| Sonnet 5 | $0.00015 | $0.00103 |
| Haiku 4.5 | $0.00007 | $0.00052 |
Grade A, and why
162-java-profiling-analyze 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 2d 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.
What it actually says
Java Profiling Workflow / Step 2 / Analyze profiling data
Analyze profiling results systematically: inventory results (flamegraphs, JFR, GC logs, thread dumps), identify problems (memory leaks, CPU hotspots, threading issues), document findings using standardized templates (profiling-problem-analysis-YYYYMMDD.md, profiling-solutions-YYYYMMDD.md), prioritize using Impact/Effort scores, and correlate multiple profiling files for validation.
What is covered in this Skill?
- Inventory: scan profiler/results/ for allocation-flamegraph, heatmap-cpu, memory-leak, *.jfr, *.log, *.txt
- Problem identification: memory (leaks, excessive allocations, GC pressure), performance (CPU hotspots, blocking), threading (deadlocks, contention, pool saturation)
- Documentation: docs/profiling-problem-analysis-YYYYMMDD.md, docs/profiling-solutions-YYYYMMDD.md
- Prioritization: Impact (1–5) / Effort (1–5), focus on high priority first
- Tools: async-profiler, JFR, JProfiler/YourKit, GCViewer, flamegraphs, heatmaps
Scope: Validate profiling results represent realistic load scenarios. Cross-reference multiple files. Include quantitative metrics.
Constraints
Validate profiling results represent realistic load before analysis. Document assumptions and limitations. Cross-reference multiple files.
- VALIDATE: Ensure profiling results represent realistic load scenarios before analysis
- DOCUMENT: Record assumptions and limitations in analysis reports
- CROSS-REFERENCE: Use multiple profiling files to validate findings
- BEFORE APPLYING: Read the reference for problem analysis and solutions templates
When to use this skill
- Analyze JFR profile
- Profile analysis
- Performance analysis
Reference
For detailed guidance, examples, and constraints, see references/162-java-profiling-analyze.md.
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.
- 2d ago First seen · 41 lines · 75 tokens per session scan A a267286d2bb1
162-java-profiling-analyze is a skill published in the GitHub repository jabrena/cursor-rules-examples (2 stars, last pushed 6d ago), licensed Apache-2.0. It adds 75 tokens to every session and 516 once invoked, about $0.0004 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.
Other skills, from other repositories
complexity
Wire and satisfy cyclomatic complexity lint. Detect the repo's existing linter, set or keep a cap (default 10), extract until green, never disable the rule. Use when complexity.mdc globs match, lint reports C901/complexity, or the user asks for simpler / less nested code.
uikit-expert
Write, review, or improve UIKit code following best practices for view controller lifecycle, Auto Layout, collection views, navigation, animation, memory management, and modern iOS 18–26 APIs. Use when building new UIKit features, refactoring existing views or view controllers, reviewing code quality, adopting modern…
debugging
Debugs difficult, intermittent, cross-layer, or regression bugs evidence before fixes. Use when the cause is unknown, normal debugging stalled, or the user asks to hunt, diagnose, or root-cause a bug.
redesign-existing-projects
Elaya audit for existing sites/apps that look generic, cheap, or AI-made. Diagnose first, then fix in place (fonts, color, states, layout, motion). Use when Mario says polish, audit, upgrade, or it looks horrible. Product apps apply diagnosis through premium-ui-craft values, not Elaya black/Geist/700ms. Upstream…
testing
Test writing workflows: TDD order, mocks, house gauntlet, regression naming. Use when writing/editing tests or when testing.mdc globs match. Thin rule = roofs; this skill = procedure.
design-stack
Router for Mario's Design agent. Picks one UI skill plus premium-ui-craft. Use at the start of any Product Designer / @Design / UX/UI turn.