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 ComeOnOliver/skillshub --skill axiom-ios-performancegit clone --depth 1 https://github.com/ComeOnOliver/skillshubWrote 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/comeonoliver/skillshub/axiom-ios-performance)<a href="https://agentmods.dev/skills/comeonoliver/skillshub/axiom-ios-performance"><img src="https://agentmods.dev/badge/skills/comeonoliver/skillshub/axiom-ios-performance/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/comeonoliver/skillshub/axiom-ios-performance"><img src="https://agentmods.dev/badge/skills/comeonoliver/skillshub/axiom-ios-performance.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 | $0.00038 | $0.03039 |
| Opus 5 | $0.00019 | $0.01520 |
| Sonnet 5 | $0.00008 | $0.00608 |
| Haiku 4.5 | $0.00004 | $0.00304 |
Grade A, and why
axiom-ios-performance 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 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.
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 — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.
iOS Performance Router
You MUST use this skill for ANY performance issue including memory leaks, slow execution, battery drain, or profiling.
When to Use
Use this router when:
- App feels slow or laggy
- Memory usage grows over time
- Battery drains quickly
- Device gets hot during use
- High energy usage in Battery Settings
- Diagnosing performance with Instruments
- Memory leaks or retain cycles
- App crashes with memory warnings
Routing Logic
Memory Issues
Memory leaks (Swift) → /skill axiom-memory-debugging
- Systematic leak diagnosis
- 5 common leak patterns
- Instruments workflows
- deinit not called
Memory leak scan → Launch memory-auditor agent or /axiom:audit memory (6 common patterns: timers, observers, closures, delegates, view callbacks, PhotoKit)
Memory leaks (Objective-C blocks) → /skill axiom-objc-block-retain-cycles
- Block retain cycles
- Weak-strong pattern
- Network callback leaks
Performance Profiling
Performance profiling (GUI) → /skill axiom-performance-profiling
- Time Profiler (CPU)
- Allocations (memory growth)
- Core Data profiling (N+1 queries)
- Decision trees for tool selection
Automated profiling (CLI) → /skill axiom-xctrace-ref
- Headless xctrace profiling
- CI/CD integration patterns
- Command-line trace recording
- Programmatic trace analysis
Run automated profile → Use performance-profiler agent or /axiom:profile
- Records trace via xctrace
- Exports and analyzes data
- Reports findings with severity
Hang/Freeze Issues
App hangs or freezes → /skill axiom-hang-diagnostics
- UI unresponsive for >1 second
- Main thread blocked (busy or waiting)
- Decision tree: busy vs blocked diagnosis
- Time Profiler vs System Trace selection
- 8 common hang patterns with fixes
- Watchdog terminations
Energy Issues
Battery drain, high energy → /skill axiom-energy
- Power Profiler workflow
- Subsystem diagnosis (CPU/GPU/Network/Location/Display)
- Anti-pattern fixes
- Background execution optimization
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 · 313 lines · 38 tokens per session scan A e584bbce3c4c
axiom-ios-performance is a skill published in the GitHub repository ComeOnOliver/skillshub (63 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 3,039 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 2026-09-03.
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