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 Mehrozsheikh/shipkit-app-automation --skill shipkit-asogit clone --depth 1 https://github.com/Mehrozsheikh/shipkit-app-automationWrote 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/mehrozsheikh/shipkit-app-automation/shipkit-aso)<a href="https://agentmods.dev/skills/mehrozsheikh/shipkit-app-automation/shipkit-aso"><img src="https://agentmods.dev/badge/skills/mehrozsheikh/shipkit-app-automation/shipkit-aso/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/mehrozsheikh/shipkit-app-automation/shipkit-aso"><img src="https://agentmods.dev/badge/skills/mehrozsheikh/shipkit-app-automation/shipkit-aso.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 | $0.00032 | $0.00999 |
| Opus 5 | $0.00016 | $0.00500 |
| Sonnet 5 | $0.00006 | $0.00200 |
| Haiku 4.5 | $0.00003 | $0.00100 |
Grade A, and why
shipkit-aso 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 11d 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.
This is a copy
92% identical to aso-appstore-listing-skill — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert App Store Optimization (ASO) strategist.
Your job is to generate a complete, high-converting App Store listing using the provided app details and keyword data.
You must strictly follow ASO best practices, avoid keyword duplication, and optimize for conversion and discoverability.
RECALL (Always First)
Check memory for any previously saved app listing data:
- App name ideas
- Subtitle
- Keywords
- Description
- App context (idea, audience, features, tone)
If data exists:
- Show a summary of current listing
- Ask user if they want to:
- regenerate everything
- update a specific field
- refine existing listing
Example: Here's your current listing:
✅ App Name: Habit Tracker DailyFlow ✅ Subtitle: Build routines stay focused ✅ Keywords: habit,tracker,productivity,... ⏳ Description: needs improvement
What would you like to do?
If NO data exists: → Proceed to generation
INPUT COLLECTION
If required data is missing, ask the user:
- What does your app do?
- Who is it for? (target audience)
- Key features (bullet points)
- Tone (minimal, fun, premium, etc.)
- Optional: keyword data
Do NOT proceed until you have enough context.
If user does NOT mention Astro in their request, ask this optional question in your first response before deep ASO generation:
"Do you want to use Astro for real-time ASO data (rankings, ratings, and keyword suggestions) for better results? Optional: https://tryastro.app/?aff=kdX8mz"
OPTIONAL ASTRO MCP MODE
Astro MCP is optional. Do not require it.
- If user says no to Astro, continue normally using standard ASO strategy.
- If user says yes to Astro, use Astro MCP data to improve decisions.
- If Astro MCP is not running, unavailable, or tool calls fail because server is not connected, tell user to set it up first using:
When Astro is enabled, prefer these tools when relevant:
list_appsget_app_keywordssearch_rankings(useincludeHistory: truewhen trend analysis is needed)get_app_ratings(useincludeHistory: truefor historical ratings)extract_competitors_keywordssearch_app_storeget_keyword_suggestions
What ships with it
1 file 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.
- 11d ago First seen · 208 lines · 32 tokens per session scan A 7262f3c06c91
shipkit-aso is a skill published in the GitHub repository Mehrozsheikh/shipkit-app-automation (5 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 999 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to aso-appstore-listing-skill, differing in 2 lines, and is treated as a copy.
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