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-energy-refgit 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-energy-ref)<a href="https://agentmods.dev/skills/comeonoliver/skillshub/axiom-energy-ref"><img src="https://agentmods.dev/badge/skills/comeonoliver/skillshub/axiom-energy-ref/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-energy-ref"><img src="https://agentmods.dev/badge/skills/comeonoliver/skillshub/axiom-energy-ref.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 | $0.06320 |
| Opus 5 | $0.00021 | $0.03160 |
| Sonnet 5 | $0.00008 | $0.01264 |
| Haiku 4.5 | $0.00004 | $0.00632 |
Grade A, and why
axiom-energy-ref 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 8d 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 — 1,105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Energy Optimization Reference
Complete API reference for iOS energy optimization, with code examples from WWDC sessions and Apple documentation.
Related skills: axiom-energy (decision trees, patterns), axiom-energy-diag (troubleshooting)
Part 1: Power Profiler Workflow
Recording a Trace with Instruments
Tethered Recording (Connected to Mac)
1. Connect iPhone wirelessly to Xcode
- Xcode → Window → Devices and Simulators
- Enable "Connect via network" for your device
2. Profile your app
- Xcode → Product → Profile (Cmd+I)
- Select Blank template
- Click "+" → Add "Power Profiler"
- Optionally add "CPU Profiler" for correlation
3. Record
- Select your app from target dropdown
- Click Record (red button)
- Use app normally for 2-3 minutes
- Click Stop
4. Analyze
- Expand Power Profiler track
- Examine per-app lanes: CPU, GPU, Display, Network
Important: Use wireless debugging. When device is charging via cable, system power usage shows 0.
On-Device Recording (Without Mac)
From WWDC25-226: Capture traces in real-world conditions.
1. Enable Developer Mode
Settings → Privacy & Security → Developer Mode → Enable
2. Enable Performance Trace
Settings → Developer → Performance Trace → Enable
Set tracing mode to "Power Profiler"
Toggle ON your app in the app list
3. Add Control Center shortcut
Control Center → Tap "+" → Add a Control → Performance Trace
4. Record
Swipe down → Tap Performance Trace icon → Start
Use app (can record up to 10 hours)
Tap Performance Trace icon → Stop
5. Share trace
Settings → Developer → Performance Trace
Tap Share button next to trace file
AirDrop to Mac or email to developer
Interpreting Power Profiler Metrics
| Lane | Meaning | What High Values Indicate |
|---|---|---|
| System Power | Overall battery drain rate | General energy consumption |
| CPU Power Impact | Processor activity score | Computation, timers, parsing |
| GPU Power Impact | Graphics rendering score | Animations, blur, Metal |
| Display Power Impact | Screen power usage | Brightness, content type |
| Network Power Impact | Radio activity score | Requests, downloads, polling |
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.
- 8d ago First seen · 1,105 lines · 42 tokens per session scan A aba0f1909be0
axiom-energy-ref is a skill published in the GitHub repository ComeOnOliver/skillshub (63 stars, last pushed 2mo ago), licensed MIT. It adds 42 tokens to every session and 6,320 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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