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 agentmods add skills/mtbun/storeshots-mcp/skillnpx skills add mtbun/storeshots-mcp --skill skillgit clone --depth 1 https://github.com/mtbun/storeshots-mcpWrote 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/mtbun/storeshots-mcp/skill)<a href="https://agentmods.dev/skills/mtbun/storeshots-mcp/skill"><img src="https://agentmods.dev/badge/skills/mtbun/storeshots-mcp/skill.svg" alt="Measured on agentmods" 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 | $0.00049 | $0.00869 |
| Opus 5 | $0.00024 | $0.00434 |
| Sonnet 5 | $0.00010 | $0.00174 |
| Haiku 4.5 | $0.00005 | $0.00087 |
Grade A, and why
storeshots 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 5d 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
storeshots — guided store screenshot workflow
Produce a complete, consistent set of store-ready marketing screenshots for an app, using the storeshots rendering tools. You do the thinking (benefits, copy, translation); the tools do the pixels.
Tooling check
Prefer the MCP tools if the storeshots MCP server is connected (list_presets, compose_screenshot, generate_set, create_showcase, validate_screenshot). If not connected, use the CLI instead: npx -y --package=storeshots-mcp storeshots <command> (run storeshots help for usage). Every step below maps 1:1 to either surface.
Phase 1 — Configuration
Ask the user, as a short checklist:
- Platforms: which presets? Offer ios-phone, android-phone, ipad-13, android-tablet, play-feature-graphic. Default: ios-phone + android-phone.
- Count: how many screenshots per platform? Default 6, max 10.
- Language(s): default English first, then translate. Note the BCP-47 codes; they control locale-correct uppercasing.
- Brand color: 6-digit hex. If a codebase is available, look for the primary/theme color and propose it instead of asking cold.
- Screenshots source: existing image files (collect paths), or guide the user through capturing simulator/emulator screenshots first.
Phase 2 — Benefit discovery
Identify one benefit per screenshot. If a codebase is available, read it and propose benefits for visually demonstrable features. Otherwise ask the user to describe the app and refine together.
Rules:
- Each headline is a verb (1-2 bold action words) plus a descriptor (2-5 words on what the user gains).
- Never feature paywall, subscription, checkout, or purchase-confirmation screens.
- Prefer screens with real-looking content over empty states.
Present the list as a table (order, verb, descriptor, planned screenshot) and iterate until the user approves. Do not render anything before approval.
Phase 3 — Render
For each platform, call generate_set with the approved items in order (or one compose_screenshot/CLI compose per item). Use the same brand color and item order across platforms so the sets match. Pass the language code via lang; supply headline text in natural case and let the tool handle uppercasing (Turkish İ, German umlauts, etc. are locale-aware).
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.
- 5d ago First seen · 54 lines · 49 tokens per session scan A 354509807498
storeshots is a skill published in the GitHub repository mtbun/storeshots-mcp (20 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 869 once invoked, about $0.0002 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.
Other skills, from other repositories
aso-playbook
Beginner-friendly App Store Optimization guide covering keyword research, screenshot design, rating management, and A/B testing for iOS and Android. By @WeiYipei — practical ASO for indie developers and small teams.
gingiris-aso-growth
🇺🇸 ASO & Mobile App Growth Playbook 2026 — Complete App Store Optimization guide. ASO keyword ranking, App Store & Google Play listing optimization, app cold start, UGC creator operations, TikTok/Instagram/YouTube Shorts marketing, AI-matrix content scaling, mobile user acquisition. 🇨🇳 ASO 增长与 App 冷启动权威指南 …
gr-aso
ASO（App Store Optimization）+ App 冷启动。覆盖关键词研究、metadata 优化、UGC 创作者矩阵、 TikTok 投流、AI 多账号矩阵、多语言本地化。从 gingiris-aso-growth 提炼。.
appshot-core
Foundation skill for Appshot. Defines the Remotion project architecture, primitives library, config schema, device presets, and store requirements. Owns the shared extraction phase used by appshot-videos and appshot-images.
appshot-images
Generate App Store and Google Play screenshot designs. Use when the user wants to create store listing images, screenshot mockups, or promotional graphics for a mobile app. Builds on appshot-core foundation.
appshot-videos
Generate App Store / Google Play preview videos using Remotion. Scans the target app's codebase, proposes custom scenes, and writes bespoke .tsx scene files using shared animation primitives. Mobile apps only (iOS/Android). Use when the user wants to create a demo video, app preview, promo video, or marketing video…