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 rshankras/claude-code-apple-skills --skill store-growth-auditgit clone --depth 1 https://github.com/rshankras/claude-code-apple-skillsWrote 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/rshankras/claude-code-apple-skills/store-growth-audit)<a href="https://agentmods.dev/skills/rshankras/claude-code-apple-skills/store-growth-audit"><img src="https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/store-growth-audit/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/rshankras/claude-code-apple-skills/store-growth-audit"><img src="https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/store-growth-audit.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 | $0.00103 | $0.03976 |
| Opus 5 | $0.00051 | $0.01988 |
| Sonnet 5 | $0.00021 | $0.00795 |
| Haiku 4.5 | $0.00010 | $0.00398 |
Grade A, and why
store-growth-audit 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 — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Store Growth Audit
Walk an app — new or live — through the full App Store growth playbook, phase by phase, and produce a scorecard: what's installed, what's missing, what to do next, and who fixes it.
The invariant: every item has a detection rule. Status comes from an ASC read, a codebase check, or an explicit question — never from vibes. If the user doesn't know, the item is 🟠 unverified, not assumed ✅.
Where it fits (read the seams)
- Not
store-signals. That is the continuous signal → backlog loop: are the numbers moving, did last cycle's bets pay off? This is the structural audit: is the machinery even installed? Run this quarterly (or pre-launch); run store-signals monthly. Trend questions route there. - Not
analytics-interpretation. Metric-quality judgments ("is 3.2% conversion good?") route there; this skill only records the baseline and whether benchmarks were checked. - Fixes never happen here. Every 🔴/🟠 routes to a named sibling skill and (when driven from
SwiftShip) an
/apple:*command. This skill detects, scores, and routes. Read-only on ASC.
When This Skill Activates
- "Audit my app's growth / store presence / what levers am I missing"
- A new app is approaching first submission and needs a growth plan, not just metadata
- Quarterly re-audit cadence, or after a launch that undershot expectations
- Before deciding to spend on paid acquisition ("is the free machinery done first?")
- Portfolio triage: "which of my apps is leaving the most on the table"
The Model: P0–P9
54 items across ten phases. Each phase is a theme; the item detail lives in the checklist files.
| Phase | Theme | Items | Goal |
|---|---|---|---|
| P0 | Day-one money toggles | 4 | Free margin + a measurement baseline before anything else |
| P1 | On-metadata ASO | 7 | Every indexed field working (title, subtitle, keywords, events, IAPs) |
| P2 | Conversion assets | 5 | Icon, screenshots, trust signals that convert impressions |
| P3 | Localization | 5 | Metadata-first market expansion + PPP pricing |
| P4 | Ratings machinery | 4 | Prompting, replying, and protecting the rating |
| P5 | Experimentation | 4 | PPO, CPPs, events as a testing habit |
| P6 | Featuring & free discovery | 6 | Nominations, new-OS adoption, storefronts, web presence |
| P7 | Paid & external traffic | 8 | Apple Ads ladder, launch spikes, pre-orders, codes |
| P8 | Earnings | 7 | Paywall experiments, win-backs, web checkout, bundles |
| P9 | Retention loop & ops | 4 | Retention surfaces + the recurring refresh calendar |
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.
- 8d ago First seen · 219 lines · 103 tokens per session scan A a5c06f48499c
store-growth-audit is a skill published in the GitHub repository rshankras/claude-code-apple-skills (719 stars, last pushed 1mo ago), licensed MIT. It adds 103 tokens to every session and 3,976 once invoked, about $0.0005 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.
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