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 kensaurus/cursor-kenji --skill plan-mobile-readinessgit clone --depth 1 https://github.com/kensaurus/cursor-kenjiWrote 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/kensaurus/cursor-kenji/plan-mobile-readiness)<a href="https://agentmods.dev/skills/kensaurus/cursor-kenji/plan-mobile-readiness"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/plan-mobile-readiness/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/kensaurus/cursor-kenji/plan-mobile-readiness"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/plan-mobile-readiness.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 | $0.00066 | $0.01794 |
| Opus 5 | $0.00033 | $0.00897 |
| Sonnet 5 | $0.00013 | $0.00359 |
| Haiku 4.5 | $0.00007 | $0.00179 |
Grade A, and why
plan-mobile-readiness 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 5d 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mobile Store-Readiness Audit + Pre-Submission Plan
Degree of freedom: HIGH — inventory A–E, score rejection risk, emit a plan. Stay plan-only. No manifest, Data Safety, or listing edits until approved.
This skill vs neighbors
| Skill | Owns |
|---|---|
| plan-mobile-readiness (this) | Store submission mechanics |
plan-aso |
Listing keywords / conversion |
plan-privacy-compliance |
Privacy labels vs real collection |
Role: Senior mobile release engineer + store-compliance specialist.
Task: Inventory build/config/listing against checklist A–E, map gaps to store
guidelines, phase remediations, emit plan-mobile-readiness.md. Audit & plan only —
no manifest, Data Safety, or listing edits until approved.
Catch the rejections before the reviewer does. Change nothing until approved.
How to reason (every plan item)
- Propose — privacy manifest, usage string, demo account, build, or listing fix
- Risk — first-pass rejection or Guideline 2.5.2 thin-app block
- Keep-working — platforms/items that already match store rules
- Phase — Privacy → Functionality → Payments+build → Listing (do not execute)
Worked example
Propose: add
PrivacyInfo.xcprivacyfor required-reason APIs; align Play Data Safety with the AdMob SDK. Risk: first-pass rejection — missing privacy manifest + Data Safety ↔ permission mismatch. Keep-working: iOS usage-description strings already present for camera/photos. Phase: Phase 1 — Privacy (blocking). Store: iOS 5.1.2 / Play Data Safety; demo account still required in Phase 2 if login-gated.
About 25% of App Store submissions are rejected on first pass — mechanical, pre-detectable causes: missing privacy manifests, Data Safety ↔ permission mismatches, no demo account, placeholder buttons, crashes on older devices, stale target API. Apple blocks prompt-to-app builders under Guideline 2.5.2 — the thin web-view rejection vibe-coded apps trip constantly.
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.
- 5d ago First seen · 173 lines · 66 tokens per session scan A 25326a660ca7
plan-mobile-readiness is a skill published in the GitHub repository kensaurus/cursor-kenji (9 stars, last pushed 11d ago), licensed MIT. It adds 66 tokens to every session and 1,794 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
flutter-pre-caching
Use when preloading fonts, asset/network images, Lottie/Rive animations, local JSON/config, warming initial API data, or optimizing Flutter Web startup.
firebase-messaging
Use when setting up Firebase Cloud Messaging, managing permissions and tokens, handling background/foreground notification taps, or dispatching messages server-side (HTTP v1).
bloc
Use when creating a Cubit or Bloc, modeling state with sealed classes or status enums, wiring BlocBuilder/BlocListener/BlocProvider, writing bloc tests, or choosing between Cubit and Bloc.
firebase-database
Use when syncing real-time data, structuring JSON trees, reading/writing, creating listeners, enabling offline persistence, managing presence, sharding, or writing security rules.
flutter-app-architecture
Use when scaffolding a project, refactoring into layers, creating view models/repositories, configuring dependency injection, or implementing unidirectional data flow (MVVM).
generate-images-with-firebase-ai
Use when generating or editing images from Flutter/Dart with Firebase AI Logic and a Gemini image model (Nano Banana), making the first call work, choosing Gemini Developer API vs Vertex AI, hitting quota, billing or App Check failures, getting empty or image-only responses, sending a user photo as input, controlling…