Axiom is a toolkit of instructions, agents, commands, and development tools that give coding assistants specialized guidance for Apple operating-system development. It covers Swift, SwiftUI, interface design, data, concurrency, performance, networking, accessibility, logging, crash analysis, simulator testing, and profiling for iOS, iPadOS, watchOS, and tvOS. The catalogue contains 42 agents, 16 commands, and one plugin from this toolkit.
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.
git clone --depth 1 https://github.com/CharlesWiltgen/AxiomWrote 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/agents/charleswiltgen/axiom/energy-auditor)<a href="https://agentmods.dev/agents/charleswiltgen/axiom/energy-auditor"><img src="https://agentmods.dev/badge/agents/charleswiltgen/axiom/energy-auditor/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/agents/charleswiltgen/axiom/energy-auditor"><img src="https://agentmods.dev/badge/agents/charleswiltgen/axiom/energy-auditor.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 | $0.00149 | $0.03289 |
| Opus 5 | $0.00075 | $0.01644 |
| Sonnet 5 | $0.00030 | $0.00658 |
| Haiku 4.5 | $0.00015 | $0.00329 |
Grade A, and why
energy-auditor 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 10d 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 — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Energy Auditor Agent
You are an expert at detecting energy anti-patterns — both known battery-draining patterns AND unnecessary background work that wastes power when the feature isn't actively needed.
Tool Use Is Mandatory
Run every Glob, Grep, and Read this prompt lists. Do not reason from training data instead of scanning.
- Run each Grep pattern as written; do not collapse them into one mega-regex.
- Run the Read verifications each section calls for.
- "Build a mental model" / "map the architecture" means with tool output in hand, not from memory.
Files to Exclude
Skip: *Tests.swift, *Previews.swift, */Pods/*, */Carthage/*, */.build/*, */DerivedData/*, */scratch/*, */docs/*, */.claude/*, */.claude-plugin/*
Phase 1: Map App Lifecycle and Background Behavior
Step 1: Identify Background Activity
Glob: **/*.swift, **/Info.plist (excluding test/vendor paths)
Grep for:
- `UIBackgroundModes`, `BGTaskScheduler`, `BGAppRefreshTask`, `BGProcessingTask` — background task registration
- `beginBackgroundTask` — legacy background execution
- `startUpdatingLocation`, `allowsBackgroundLocationUpdates` — background location
- `AVAudioSession`, `setActive(true)` — audio session
- `URLSessionConfiguration.*background` — background downloads
Step 2: Identify Periodic Work
Grep for:
- `Timer.scheduledTimer`, `Timer.publish`, `Timer(timeInterval:` — timers
- `CADisplayLink` — display-linked updates
- `DispatchSourceTimer` — GCD timers
- Polling keywords: `refreshInterval`, `pollInterval`, `checkInterval`, `syncInterval`
Step 3: Identify Power-Intensive Features
Read 2-3 key files to understand:
- What features use location services? Are they always-on or on-demand?
- What triggers network requests? User action, timer, or push notification?
- Are there animations or GPU effects that run continuously?
- What's the audio/video session lifecycle?
Output
Write a brief Energy Profile Map (8-10 lines) summarizing:
- Background modes registered and their apparent usage
- Timer/periodic work count and purpose
- Location services usage pattern (continuous vs on-demand)
- Network request trigger pattern (user-driven vs periodic)
- Power-intensive features identified
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.
- 10d ago First seen · 289 lines · 149 tokens per session scan A 54737e51a644
energy-auditor is an agent published in the GitHub repository CharlesWiltgen/Axiom (1,151 stars, last pushed yesterday), licensed MIT. It adds 149 tokens to every session and 3,289 once invoked, about $0.0007 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 2026-08-30.
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