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 SteveGJones/ai-first-sdlc-practices --skill ios-appstore-submitgit clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practicesWrote 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/stevegjones/ai-first-sdlc-practices/ios-appstore-submit)<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/ios-appstore-submit"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/ios-appstore-submit/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/stevegjones/ai-first-sdlc-practices/ios-appstore-submit"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/ios-appstore-submit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00053 | $0.01008 |
| Opus 5 | $0.00026 | $0.00504 |
| Sonnet 5 | $0.00011 | $0.00202 |
| Haiku 4.5 | $0.00005 | $0.00101 |
Grade A, and why
ios-appstore-submit 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
iOS App Store Submit
A pre-submission audit that catches the issues most likely to get an App Store submission rejected,
before you hit "Submit for Review". Belongs to the ios-release-engineer discipline. Run it once
the build is on TestFlight and you're preparing the public release.
Arguments
path-to-ios-project— the project directory to check (defaults to the current directory).
Steps
1. Run the pre-flight checks
python -m ios_preflight.cli <project-dir> [--uses-push]
Resolve every ERROR (missing usage descriptions, missing privacy manifest when required,
get-task-allow in release). Address WARNINGs (export compliance, placeholder purpose strings)
too — they cause stalled uploads and review friction.
2. Clear the three privacy surfaces (all can block the submission)
- App Privacy nutrition labels (declared in App Store Connect) — data types collected, whether linked to identity, used for tracking, and purpose. Must include data collected by third-party SDKs. A new version can't ship with this incomplete.
- Privacy manifest (
PrivacyInfo.xcprivacyin the bundle) — tracking flag, tracking domains, collected data types, and required-reason API declarations with approved reason codes. Enforced at upload. - Purpose strings + ATT — every
NS…UsageDescriptionpresent and human-readable; call ATT before touching the IDFA, and keep it consistent with the nutrition label / manifest tracking declaration. - A privacy policy URL must be live and reachable.
3. Check the high-frequency rejection guidelines
(Guideline numbers change — re-verify against the live App Review Guidelines.)
- 2.1 Completeness — no crashes on review, no placeholder content, no broken links; provide a demo account if there's a login.
- 2.3 Accurate metadata — screenshots/description match the app; no misleading keywords.
- 3.1.1 In-App Purchase — digital goods/content sold through IAP, not external payment.
- 4.2 Minimum functionality — not a thin web-wrapper with no native value.
- 4.8 Login services — if you offer social/third-party login, offer a privacy-preserving option (e.g. Sign in with Apple) where required; on account deletion, revoke SiwA tokens via the REST API.
- 5.1.1(v) Account deletion — if the app supports account creation, it must offer in-app account deletion (delete, not just deactivate), easy to find.
- 5.1.1 / 5.1.2 Data — request only data you need, with justification.
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 · 83 lines · 53 tokens per session scan A bfb5890b45cc
ios-appstore-submit is a skill published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 1,008 once invoked, about $0.0003 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.
Other skills, from other repositories
play-policy-insights
Automated auditor designed to verify Android applications against Google Play Policy domains. It cross-references static code analysis with Play Store declarations to generate deterministic compliance reports, identifying undeclared data collection, architectural risks, and missing disclosures across Permissions and…
app-store-preflight-compliance
Pre-submission compliance scanner workflow for Apple App Store apps. Use when reviewing iOS, macOS, tvOS, watchOS, or visionOS projects (Swift, Objective-C, React Native, Expo) for App Store rejection risks, submission readiness, privacy compliance, or guideline violations.
app-store-review
Evaluates code against Apple's App Store Review Guidelines. Use this skill when reviewing iOS, macOS, tvOS, watchOS, or visionOS app code (Swift, Objective-C, React Native, or Expo) to identify potential App Store rejection issues before submission. Triggers on tasks involving app review preparation, compliance…
account-deletion
Generates an Apple-compliant account deletion flow with multi-step confirmation UI, optional data export, configurable grace period, Keychain cleanup, and server-side deletion request. Use when user needs account deletion, right-to-delete, or Apple App Review compliance for account removal.
consent-flow
Generates GDPR/CCPA/DPDP privacy consent flows with granular category preferences, consent state persistence, audit logging, and ATT (App Tracking Transparency) integration. Use when user needs privacy consent UI, cookie/tracking consent, or compliance management.
appstore-review-checker
Audit iOS/macOS apps against App Store Review Guidelines before submission, with evidence-backed verdicts and fixes. Don't use for Google Play, general code review, or rejection appeals.