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-performance-profilinggit 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-performance-profiling)<a href="https://agentmods.dev/skills/comeonoliver/skillshub/axiom-performance-profiling"><img src="https://agentmods.dev/badge/skills/comeonoliver/skillshub/axiom-performance-profiling/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-performance-profiling"><img src="https://agentmods.dev/badge/skills/comeonoliver/skillshub/axiom-performance-profiling.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 | $0.00058 | $0.08087 |
| Opus 5 | $0.00029 | $0.04043 |
| Sonnet 5 | $0.00012 | $0.01617 |
| Haiku 4.5 | $0.00006 | $0.00809 |
Grade A, and why
axiom-performance-profiling scanned grade A 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
let tracks = try context.fetch(Track.fetchRequest()) How it starts
The opening of the file, as written. The whole thing — 1,042 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Profiling
Overview
iOS app performance problems fall into distinct categories, each with a specific diagnosis tool. This skill helps you choose the right tool, use it effectively, and interpret results correctly under pressure.
Core principle: Measure before optimizing. Guessing about performance wastes more time than profiling.
Requires: Xcode 15+, iOS 14+
Related skills: axiom-swiftui-performance (SwiftUI-specific profiling with Instruments 26), axiom-memory-debugging (memory leak diagnosis)
When to Use Performance Profiling
Use this skill when
- ✅ App feels slow (UI lags, loads take 5+ seconds)
- ✅ Memory grows over time (Xcode shows increasing memory usage)
- ✅ Battery drains fast (device gets hot, battery depletes in hours)
- ✅ You want to profile proactively (before users complain)
- ✅ You're unsure which Instruments tool to use
- ✅ Profiling results are confusing or contradictory
Use axiom-memory-debugging instead when
- Investigating specific memory leaks with retain cycles
- Using Instruments Allocations in detail mode
Use axiom-swiftui-performance instead when
- Analyzing SwiftUI view body updates
- Using SwiftUI Instrument specifically
Performance Decision Tree
Before opening Instruments, narrow down what you're actually investigating.
Step 1: What's the Symptom?
App performance problem?
├─ App feels slow or lags (UI interactions stall, scrolling stutters)
│ └─ → Use Time Profiler (measure CPU usage)
├─ Memory grows over time (Xcode shows increasing memory)
│ └─ → Use Allocations (measure object creation)
├─ Data loading is slow (parsing, database queries, API calls)
│ └─ → Use Core Data instrument (if using Core Data)
│ └─ → Use Time Profiler (if it's computation)
└─ Battery drains fast (device gets hot, depletes in hours)
└─ → Use Energy Impact (measure power consumption)
Step 2: Can You Reproduce It?
YES – Use Instruments to measure it (profiling is most accurate)
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 · 1,042 lines · 58 tokens per session scan A bb6ced6deea1
axiom-performance-profiling is a skill published in the GitHub repository ComeOnOliver/skillshub (63 stars, last pushed 2mo ago), licensed MIT. It adds 58 tokens to every session and 8,087 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
agent-introspection-debugging
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
dx-audit
Audits libraries, CLIs, and SDKs using 38 rules for public contracts, package exports, piped output, errors, and configuration. Use when asked to "audit my CLI", "review my SDK", "make this agent-friendly", or diagnose package type resolution. For agentic product trust use ax-audit; for docs use docs-writing.
instance-performance-triage
Answer "the instance is slow" or "my nightly job never ran" from ServiceNow's own telemetry — transaction logs, syslog, systrigger, progress workers, execution trackers — instead of ad-hoc scripts that add to the load.
blast-radius
Trace ServiceNow configuration dependencies — what artifacts touch a given field, what calls a script include, table/app-level config inventory. Use before deletes, renames, or refactors.
incident-management
Manage ServiceNow incidents — creation with impact/urgency priority calc, auto-assignment by category, reassignment tracking, major incident declaration with bridge calls, time-based escalation, MTTR metrics.
problem-management
Manage ServiceNow problems — create from linked incidents, proactive pattern detection, RCA with 5-Whys, knownerror workarounds (KEDB), KEDB search by CI/category/keywords, and permanent-fix linkage to changes.