appllama-usage
Use the Appllama MCP (mcp.appllama.io) well — research real top-grossing mobile apps, their screens, flows, and UI elements, then build from what you learn. Load when the Appllama MCP is connected and the task involves building a mobile app or screen, researching app design patterns, studying onboarding/paywall/feature flows, improving an existing screen, or whenever an appllama / searchapps / listappscreens tool is available. Covers the tool map, pagination, expiring media, and the full build-from-research playbooks.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/appllama/appllama-skills --skill appllama-usage- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads appllama-usage automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
Appllama Usage Skill
Appllama is the design library of top-grossing mobile apps — their real screens, flows, and UI patterns, with revenue and download context. The MCP puts that library in an agent's hands: not just a research tool, a builder's tool. You study what already wins, then you build something better.
Pair this skill with appllama-app-design-skill for every design/implementation step — this skill tells you what to study; that one tells you how to build.
Ground rules (read first)
- Start with
get_credits— it's free. It tells you the balance, limits, and reset date. Pro includes 1,500 credits a month (they reset in full on the 1st, UTC); every other call spends 1 credit. - Go deep. Design language lives in the whole journey, not a sample — walk every screen of the apps that matter for the task, images included. That is exactly what the library is for. The one thing that's against the terms is harvesting: sweeping the catalog to extract the dataset itself rather than to answer a real task. That isn't research, and it's detected server-side.
- Media URLs expire in ~1 hour. Download/view what you study promptly. If links died mid-task, re-request that page for fresh ones — screen ids are durable, links are not.
- Ignore the watermark. Every Appllama image and video carries a small Appllama watermark in the top-left corner. It is provenance, not part of the screen — don't let it skew your read of that corner (status bar, back button, title), and never reproduce it in anything you build.
- Pagination is sequential. Every list response carries
next_cursor; pass it back to continue. You cannot jump to page N — and a cursor only works for the same query that minted it. If a cursor errors, drop it and restart from page one. - If you hit a rate limit, wait it out. The per-minute and per-day limits sit far above real research; on the rare hit, wait the stated time — don't retry-hammer.
- Errors are instructions. Tool errors are written to be acted on (expired cursor → restart; out of credits → tell the user their credits reset on the 1st and they can request more in Settings → Usage).
Tool map
| Tool | What it gives you | Typical use |
|---|---|---|
get_credits | Balance, limits, reset date. Free. | Session start |
search_apps | 10 apps/page: name, revenue, downloads, rating, launch date, screens count, flow list with screen counts. Natural-language query + filters (revenue/downloads/rating/launch date/price/onboarding steps) + sort + board_id | Find the top apps for a category or need |
get_app | One app in full: ratings breakdown, category rank, IAP pricing, top countries, flows | Decide if an app deserves a deep study |
list_app_screens | 10 screens/page in journey order (welcome → onboarding → paywall → product), each with media URL, flow, UI elements, colors. Filter by flow or section | Walk an app screen by screen |
search_screens | Screens across the whole library. mode="keyword" matches screen names + filters (flow, screen_type, element, app_id); mode="semantic" searches by meaning/visual language | Gather design references for one screen type |
get_screen | One screen in full + up to 5 visually similar screens from other apps. Accepts screen_ref = app_id/screen_id (what appllama.io's "Copy Screen ID" produces) | The user pasted a screen ref; or drill into one reference |
list_flows | The flow taxonomy with screen/app counts | Discover what flows exist for a category |
get_flow_apps | Apps containing a flow, top revenue first | Find the best examples of one flow |
list_ui_elements | ~38 UI-element families with counts (one call) | Vocabulary for element-level research |
get_element_screens | Screens featuring an element family | Study how winners build one component |
list_my_boards | The member's own appllama.io boards (screens / apps / flows) | Find their curation first |
get_board | A board's full contents: screens with media, app profiles, or (app, flow) pairs | When the member curated a board for the task, START from it |
The screen_ref handshake: members can click "Copy Screen ID" on any
screen at appllama.io and paste it to you. It looks like
1393061654/spl_9i075 — feed it straight to
get_screen(screen_ref=...) and you're looking at exactly the screen they
mean, plus its closest siblings across the library.
The playbooks
| Scenario | Reference |
|---|---|
| Build an app from scratch (e.g. "build me a habit tracker") | references/build-from-scratch.md |
| Make an existing screen better | references/improve-a-screen.md |
| Flow & element research; general research method | references/research-methods.md |
Both build playbooks end the same way: the simulator loop from appllama-app-design-skill, repeated until you cannot find a flaw. Research without that loop is decoration.
Local reference boards
When you pull screens for study, save them into a local working structure — links expire in about an hour, but your notes and downloads don't:
research/
<category>/
apps.md # the shortlist: metrics, flows, verdicts
<app-name>/
screens.md # per-screen notes: id, name, flow, elements, colors
img/ # downloaded screens, in journey order
patterns.md # cross-app synthesis: the category's design language
Download the screens as you study them — synthesis happens with the images side by side, not from metadata. Notes and screen IDs are durable; re-fetch a fresh link from the ID if you ever need the pixels again.
FAQ
What does the appllama-usage skill do?
Use the Appllama MCP (mcp.appllama.io) well — research real top-grossing mobile apps, their screens, flows, and UI elements, then build from what you learn. Load when the Appllama MCP is connected and the task involves building a mobile app or screen, researching app design patterns, studying onboarding/paywall/feature flows, improving an existing screen, or whenever an appllama / searchapps / listappscreens tool is available. Covers the tool map, pagination, expiring media, and the full build-from-research playbooks.
How do I install appllama-usage?
Run npx skills add https://github.com/appllama/appllama-skills --skill appllama-usage in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/appllama-usage/ (personal) or .claude/skills/appllama-usage/ (project).
Which AI agents can use appllama-usage?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is appllama-usage safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains appllama-usage?
It is published by appllama in appllama/appllama-skills. It has 4,096 recorded installs.
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