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 kelvinkosbab/AppBootstrapAI --skill store-compliance-progit clone --depth 1 https://github.com/kelvinkosbab/AppBootstrapAIWrote 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/kelvinkosbab/appbootstrapai/store-compliance-pro)<a href="https://agentmods.dev/skills/kelvinkosbab/appbootstrapai/store-compliance-pro"><img src="https://agentmods.dev/badge/skills/kelvinkosbab/appbootstrapai/store-compliance-pro/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/kelvinkosbab/appbootstrapai/store-compliance-pro"><img src="https://agentmods.dev/badge/skills/kelvinkosbab/appbootstrapai/store-compliance-pro.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 | $0.00117 | $0.01417 |
| Opus 5.5 | $0.00047 | $0.00567 |
| Sonnet 5.5 | $0.00023 | $0.00283 |
| Haiku 4.5 | $0.00012 | $0.00142 |
Grade A, and why
store-compliance-pro 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 today.
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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Find what will get an app rejected or removed in a specific region before App Review does, and fix it when it already has. This is the deep companion to the always-on apple-regional-compliance.md and android-regional-compliance.md rules. The rules steer while writing; this skill audits the whole app plus its listing, and runs the rejection-response playbook.
Pick the mode from the request:
- Audit: before a release, before adding a storefront or country, or after adding an AI provider, payments, or another regulated feature. Run
references/audit.mdand check each in-scope region againstreferences/regions.md. - Respond: a submission was rejected or removed for a region. Follow
references/rejection-response.md: classify the finding, choose a fix, sweep the app and listing, and draft the reply. - Set up: no register exists yet. Create
docs/compliance/regions.mdand theRegionPolicyseam perreferences/rejection-response.md("Register and policy seam").
If doing a partial task, load only the relevant reference file.
Core Instructions
- Region is decided per storefront, and the store decides. Legal scope follows the App Store storefront or the Play account country, never device locale, SIM, or IP. Gating on locale is a finding.
- The listing is part of the submission. Audit metadata (name, subtitle, keywords, descriptions, promotional text, release notes, screenshots, previews) in every locale, and remember an unlocalized storefront shows the primary language.
- Third-party AI brands are the top regional trigger. ChatGPT, OpenAI, Claude, Anthropic, Gemini, Grok, Copilot, DeepSeek, Llama, and similar names in user-facing strings or metadata are a China rejection and a trademark risk everywhere. Code identifiers and dependency names are fine; consent screens may name the provider but must be region-gated with the feature.
- One policy seam. Regulated features ask a single injected
RegionPolicy. Scattered country-code comparisons, or none at all, are findings. - Prefer the fix that removes the risk. Excluding a storefront, or a build flavor without the feature, beats runtime gating when the law forbids the feature outright; runtime gating still ships the strings and SDKs.
- Never invent a license or filing number, never advise misleading reviewers, and never suggest geo-evasion (VPN-only detection, hiding features from review accounts). Compliance claims in review notes must be true.
- Mark uncertainty. Regulations change; cite the guideline or policy section and say when a requirement should be re-checked against the current text.
- Severity by consequence: blocking (will be rejected or removed in a storefront you ship to: AI brand mentions for China, missing ICP or game license, missing EU trader status, licensed feature without a license, data collected before consent on Chinese Android stores) > exposure (gated on locale instead of storefront, unknown storefront fails open, regulated feature reachable from a shortcut or notification, no register) > hygiene (provider names in strings that are currently gated, a register missing a "last verified" date).
- Cross-reference, don't duplicate: age ratings and privacy manifests go to
apple-testflight-deployment.md; Data safety toandroid-play-beta-deployment.md; AI consent and provider wiring toapple-foundation-models.mdandandroid-ai-best-practices.md; generic strings to the localization rules.
What ships with it
3 files 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.
- today First seen · 62 lines · 117 tokens per session scan A 5d22177fab6d
store-compliance-pro is a skill published in the GitHub repository kelvinkosbab/AppBootstrapAI (7 stars, last pushed yesterday), licensed MIT. It adds 117 tokens to every session and 1,417 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-10-16.
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