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 MartinPuli/createAnApp --skill apple-product-specgit clone --depth 1 https://github.com/MartinPuli/createAnAppWrote 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/martinpuli/createanapp/apple-product-spec)<a href="https://agentmods.dev/skills/martinpuli/createanapp/apple-product-spec"><img src="https://agentmods.dev/badge/skills/martinpuli/createanapp/apple-product-spec/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/martinpuli/createanapp/apple-product-spec"><img src="https://agentmods.dev/badge/skills/martinpuli/createanapp/apple-product-spec.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 | $0.00066 | $0.00687 |
| Opus 5 | $0.00033 | $0.00344 |
| Sonnet 5 | $0.00013 | $0.00137 |
| Haiku 4.5 | $0.00007 | $0.00069 |
Grade A, and why
apple-product-spec 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 9d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apple Product Spec
Turn the market thesis into a testable product contract. Every public promise must map to a real release behavior and test.
Establish the product contract
Define:
- target user, buyer, job, context, and moment of use;
- one-sentence value proposition without “AI” unless AI itself is user value;
- core loop and time-to-first-value;
- free, paid, and unavailable capabilities;
- supported device families, orientations, minimum OS, offline behavior, and accessibility target;
- explicit v1 non-goals;
- measurable success, stop, and rollback conditions.
Specify complete journeys
For each journey, include entry, prerequisites, happy path, cancellation, empty/loading/error/offline states, persistence, destructive confirmation, accessibility, analytics event if any, and acceptance tests.
Cover onboarding, core job, save/relaunch, import/export/share, settings/support/legal, permissions, paywall, purchase, restore, entitlement changes, and account/data deletion if applicable.
Define monetization as behavior
For every product or subscription, specify immutable product ID convention, entitlement, duration/type, price hypothesis, ongoing value, free limits, upgrade/downgrade relationship, restore, grace/billing retry, expiration/refund/revocation, family sharing decision, server dependency, offline cache, and customer-visible copy.
Do not sell a subscription without credible continuing value. Do not promise a trial or price until App Store Connect is configured identically.
Build the data and risk maps
For each data type, record source, purpose, device storage, transmission, processor, retention, deletion, backup, encryption, permissions, privacy-label category, and policy text. Include SDK and website data.
Identify safety, privacy, security, IP, claims, child/health/financial, user-content, moderation, AI, and platform risks. Convert each into prevention, detection, response, owner, and stop-ship rule.
Choose architecture from constraints
What ships with it
2 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.
- 9d ago First seen · 63 lines · 66 tokens per session scan A 29bfde06bb3d
apple-product-spec is a skill published in the GitHub repository MartinPuli/createAnApp (14 stars, last pushed 19d ago), licensed MIT. It adds 66 tokens to every session and 687 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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