Blitz is a native macOS application that connects AI agents to App Store Connect for managing and submitting iOS apps. Developers use it to control parts of the iOS release process, including simulator runs, in-app purchases, screenshots, TestFlight testers, and review submissions. The catalogue includes skills, an instruction, and an MCP connection for operating Blitz.
Borrowing it
Nothing to install: this file belongs to blitzdotdev/blitz-mac. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/blitzdotdev/blitz-mac/master/.claude/skills/asc-privacy-nutrition-labels/SKILL.mdgit clone --depth 1 https://github.com/blitzdotdev/blitz-macWrote 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/blitzdotdev/blitz-mac/asc-privacy-nutrition-labels)<a href="https://agentmods.dev/skills/blitzdotdev/blitz-mac/asc-privacy-nutrition-labels"><img src="https://agentmods.dev/badge/skills/blitzdotdev/blitz-mac/asc-privacy-nutrition-labels.svg" alt="Measured on agentmods" 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 | $0.00063 | $0.02215 |
| Opus 5 | $0.00032 | $0.01107 |
| Sonnet 5 | $0.00013 | $0.00443 |
| Haiku 4.5 | $0.00006 | $0.00221 |
Grade A, and why
asc-privacy-nutrition-labels 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 8d 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 — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.
asc privacy nutrition labels
Use this skill to configure App Store privacy nutrition labels for an app. This is the "App Privacy" section in App Store Connect where you declare what data your app collects, what purposes it's used for, and how it's protected.
When to use
- User says "set up privacy labels", "configure nutrition labels", "app privacy", "data collection declaration"
- The submission readiness checklist shows "Privacy Nutrition Labels" as incomplete
- User is preparing an app for first submission and needs to declare data practices
- User needs to update privacy declarations after adding new data collection
Preconditions
- Web session authenticated (cached in keychain from prior
asc web auth login, or callasc_web_authMCP tool) - Know your app ID (
ASC_APP_IDor--app)
Data Model
Each privacy declaration is a tuple of three dimensions:
Categories (what data is collected)
Grouped by type:
| Grouping | Categories |
|---|---|
| CONTACT_INFO | NAME, EMAIL_ADDRESS, PHONE_NUMBER, PHYSICAL_ADDRESS, OTHER_CONTACT_INFO |
| HEALTH_AND_FITNESS | HEALTH, FITNESS |
| FINANCIAL_INFO | PAYMENT_INFORMATION, CREDIT_AND_FRAUD, OTHER_FINANCIAL_INFO |
| LOCATION | PRECISE_LOCATION, COARSE_LOCATION |
| SENSITIVE_INFO | SENSITIVE_INFO |
| CONTACTS | CONTACTS |
| USER_CONTENT | EMAILS_OR_TEXT_MESSAGES, PHOTOS_OR_VIDEOS, AUDIO, GAMEPLAY_CONTENT, CUSTOMER_SUPPORT, OTHER_USER_CONTENT |
| BROWSING_HISTORY | BROWSING_HISTORY |
| SEARCH_HISTORY | SEARCH_HISTORY |
| IDENTIFIERS | USER_ID, DEVICE_ID |
| PURCHASES | PURCHASE_HISTORY |
| USAGE_DATA | PRODUCT_INTERACTION, ADVERTISING_DATA, OTHER_USAGE_DATA |
| DIAGNOSTICS | CRASH_DATA, PERFORMANCE_DATA, OTHER_DIAGNOSTIC_DATA |
| OTHER_DATA | OTHER_DATA_TYPES |
Purposes (why it's collected)
| Purpose ID | Meaning |
|---|---|
APP_FUNCTIONALITY |
Required for the app to work |
ANALYTICS |
Used for analytics |
PRODUCT_PERSONALIZATION |
Used to personalize the product |
DEVELOPERS_ADVERTISING |
Used for developer's advertising |
THIRD_PARTY_ADVERTISING |
Used for third-party advertising |
OTHER_PURPOSES |
Other purposes |
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.
- 8d ago First seen · 282 lines · 63 tokens per session scan A 9cbc3a8b3c2a
asc-privacy-nutrition-labels is a skill published in the GitHub repository blitzdotdev/blitz-mac (1,746 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 63 tokens to every session and 2,215 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 2026-08-30.
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