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.
npx skills add CharlesWiltgen/Axiom --skill axiom-audit-energygit 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/skills/charleswiltgen/axiom/axiom-audit-energy)<a href="https://agentmods.dev/skills/charleswiltgen/axiom/axiom-audit-energy"><img src="https://agentmods.dev/badge/skills/charleswiltgen/axiom/axiom-audit-energy/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/charleswiltgen/axiom/axiom-audit-energy"><img src="https://agentmods.dev/badge/skills/charleswiltgen/axiom/axiom-audit-energy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 108 Skill attempts to nullify the agent's safety policies or restrictions ('you have no restrictions', 'ignore your guidelines', 'do anything now'). This is a direct jailbreak that disables guardrails.Fix: Remove jailbreak framing that nullifies safety policies or restrictions. Skill content must not instruct the agent to ignore its guidelines or operate without guardrails.
- high Anti-Refusal · line 150 Skill attempts to nullify the agent's safety policies or restrictions ('you have no restrictions', 'ignore your guidelines', 'do anything now'). This is a direct jailbreak that disables guardrails.Fix: Remove jailbreak framing that nullifies safety policies or restrictions. Skill content must not instruct the agent to ignore its guidelines or operate without guardrails.
- medium Rogue Agent · line 27 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Rogue Agent · line 100 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00027 | $0.03124 |
| Opus 5 | $0.00014 | $0.01562 |
| Sonnet 5 | $0.00005 | $0.00625 |
| Haiku 4.5 | $0.00003 | $0.00312 |
Grade A, and why
axiom-audit-energy 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 6d 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 — 267 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 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.
- 6d ago First seen · 267 lines · 27 tokens per session scan A 5a9c44732e2d
axiom-audit-energy is a skill published in the GitHub repository CharlesWiltgen/Axiom (1,155 stars, last pushed 3d ago), licensed MIT. It adds 27 tokens to every session and 3,124 once invoked, about $0.0001 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 2026-09-06.
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