mobile-analyzer

mobile-analyzer is a skill for Claude Code from reatlat/fullstory-claude-plugin. It costs 43 tokens per session (1,520 once invoked), scanned A, original, MIT.

A tool for checking how people use a website or app on phones and tablets, including touch input, screen sizes, scrolling, and responsive layouts.

In plain words
What is it for?
Use it to compare mobile and desktop behavior, investigate responsive-design bugs, and find mobile-specific problems in flows such as checkout.
Why use it?
A page that works on a desktop can be difficult to use on a small touchscreen—for example, buttons may overlap or the keyboard may cover a form field.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the fullstory-reatlat plugin — 46 skills, 3 agents, 1 MCP server shipped together

Good fit Use it to compare mobile and desktop behavior, investigate responsive-design bugs, and find mobile-specific problems in flows such as checkout.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/reatlat/fullstory-claude-plugin/mobile-analyzer
Install

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.

Any agent
npx skills add reatlat/fullstory-claude-plugin --skill mobile-analyzer
Clone the repo
git clone --depth 1 https://github.com/reatlat/fullstory-claude-plugin

Made for: Claude Code.

Or install fullstory-reatlat, the plugin that ships this one along with the rest of its 46 skills, 3 agents, 1 MCP server.

Wrote 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.

agentmods badge for mobile-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/reatlat/fullstory-claude-plugin/mobile-analyzer/github.svg)](https://agentmods.dev/skills/reatlat/fullstory-claude-plugin/mobile-analyzer)
Your own site
<a href="https://agentmods.dev/skills/reatlat/fullstory-claude-plugin/mobile-analyzer"><img src="https://agentmods.dev/badge/skills/reatlat/fullstory-claude-plugin/mobile-analyzer/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.

agentmods 80×15 button for mobile-analyzer

Your own site · 80×15
<a href="https://agentmods.dev/skills/reatlat/fullstory-claude-plugin/mobile-analyzer"><img src="https://agentmods.dev/badge/skills/reatlat/fullstory-claude-plugin/mobile-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,520 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.01520
Opus 5.5 $0.00017 $0.00608
Sonnet 5.5 $0.00009 $0.00304
Haiku 4.5 $0.00004 $0.00152

Measured 7d ago against content hash e37049b1e202, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

mobile-analyzer 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 7d 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.

skills/mobile-analyzer/SKILL.md · 145 lines

How it starts

The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Mobile Analyzer

Deep-dive into mobile user experience — touch events, viewport issues, responsive design bugs, and mobile-specific conversion patterns.

When to Use

  • "How does our mobile experience compare to desktop?"
  • "Are mobile users having trouble with the checkout flow?"
  • "Find sessions where mobile users encountered viewport issues"
  • "Is the new responsive design working on tablets?"
  • "What percentage of rage clicks happen on mobile vs desktop?"
  • "Show me mobile sessions where users pinch-zoomed repeatedly"

Mental Model

Mobile users are different from desktop users:

  • Input: Touch targets, swipe gestures, virtual keyboard
  • Viewport: Smaller screen, variable sizes, landscape/portrait
  • Context: On-the-go, distracted, slower connections
  • Expectations: Faster, simpler, thumb-friendly

A design that works on desktop can fail catastrophically on mobile — elements overlapping, touch targets too small, keyboard covering form fields, horizontal scroll appearing.

For visual checks, follow session-review: open with fullstory:review-open, pass its client_id to fullstory:review-snapshot at the target timestamp, and always call fullstory:review-close, including on errors. Delegate repeated captures to session-replay.

Use free fullstory:discover_groups and fullstory:get_opportunity_stats for live signals. Discovery accepts one scope at a time (page_id, domain, app_name, segment_id, or funnel_id); use a segment for device/user filters and the live schema for time ranges. Use computed metrics for exact custom windows.

Workflow

Step 1: Quantify mobile vs desktop

Start with the split:

fullstory:build_metric(
  query="sessions by device type",
  output_type="top_n"
)
→ "68% desktop, 28% mobile, 4% tablet"

Then compare key metrics across devices:

fullstory:build_metric(query="checkout conversion by device type", output_type="top_n")
fullstory:compute_metric(metric_id)

Step 2: Mobile-specific frustration signals

Read the full file on GitHub · 145 lines

Changes

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.

  1. 7d ago Changed · +4 lines e37049b1e202
  2. 2mo ago First seen · 141 lines · 43 tokens per session scan A 960c87d7dd76

Subscribe to this mod's changes

mobile-analyzer is a skill published in the GitHub repository reatlat/fullstory-claude-plugin (35 stars, last pushed 7d ago), licensed MIT. It adds 43 tokens to every session and 1,520 once invoked, about $0.0002 per session on Opus 5.5. 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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