OpenTagViewer: Skill for Claude Code

.claude/skills/device-screenshots/SKILL.md

device-screenshots is a skill for Claude Code from parawanderer/OpenTagViewer. It costs 57 tokens per session (1,229 once invoked), scanned A, original, MIT.

A workflow for capturing screenshots from an Android app running on a Gradle-managed test device and combining them into smaller comparison sheets.

In plain words
What is it for?
Use it when changing colours, themes, images, layouts, or other visible parts of an Android app, and when comparing screenshots in light and dark modes.
Why use it?
Raw screenshots can be large, mostly empty, and expensive for an AI to inspect. The sheets make before-and-after visual checks easier and cheaper.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: reads .claude/ paths; mentions AGENTS.md.

This is parawanderer/OpenTagViewer's own configuration. It tells Claude Code how to work on OpenTagViewer itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything OpenTagViewer configures →

Reuse

Borrowing it

Nothing to install: this file belongs to parawanderer/OpenTagViewer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/parawanderer/OpenTagViewer/main/.claude/skills/device-screenshots/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/parawanderer/OpenTagViewer

Made for: Claude Code.

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 device-screenshots

README.md
[![agentmods](https://agentmods.dev/badge/skills/parawanderer/opentagviewer/device-screenshots/github.svg)](https://agentmods.dev/skills/parawanderer/opentagviewer/device-screenshots)
Your own site
<a href="https://agentmods.dev/skills/parawanderer/opentagviewer/device-screenshots"><img src="https://agentmods.dev/badge/skills/parawanderer/opentagviewer/device-screenshots/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 device-screenshots

Your own site · 80×15
<a href="https://agentmods.dev/skills/parawanderer/opentagviewer/device-screenshots"><img src="https://agentmods.dev/badge/skills/parawanderer/opentagviewer/device-screenshots.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,229 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 $0.00057 $0.01229
Opus 5 $0.00028 $0.00615
Sonnet 5 $0.00011 $0.00246
Haiku 4.5 $0.00006 $0.00123

Measured 9d ago against content hash 0f9c68648916, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

device-screenshots 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 9d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (blur.py, sheet.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.claude/skills/device-screenshots/SKILL.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Looking at the app's UI

Two halves: getting a screenshot off the device, and reading it cheaply. The second is the part that is easy to get wrong.

Never Read a raw screenshot

A device screenshot is ~1080px wide and mostly whitespace. Reading one costs a lot of vision tokens for a picture whose informative part is a few hundred pixels, and reading a before/after pair separately doubles it for a comparison that wants to be side by side anyway.

Run them through the sheet tool first:

python .claude/skills/device-screenshots/sheet.py \
    app/build/outputs/managed_device_android_test_additional_output/debug/testEmulator \
    <scratchpad>/shots

Then Read the sheets it prints. One subject, all its variants, one image, a few hundred pixels wide.

Files are grouped on the part before the last hyphen; the part after is the variant label:

my_device_list_item-fixed.png       ->  subject my_device_list_item, variant "fixed"
my_device_list_item-wallpaper.png                                    variant "wallpaper"
Flag Default For
--width 420 target width per panel
--max-height 420 cap, so a tall image cannot produce a 2000px sheet
--dark dark,wallpaper_dark,night variants composited over black rather than white

Needs Pillow (python -m pip install pillow).

Screenshots that go somewhere public

A capture destined for the wiki or an issue is a screenshot of a real build on a real device, and some of what is on it belongs to whoever took it. The AMap key dialog is the worked example: it prints the package name and signing fingerprint, because that is exactly what AMap's console asks you to paste — correct behaviour, and not something to publish.

py -3 .claude/skills/device-screenshots/blur.py shot.png --band 0.42 0.55

--band takes fractions of the height, so it survives a change of device resolution; repeat it for more than one strip. Blur rather than crop — a cropped dialog looks like it has fewer fields than it does, and the next person wonders what was removed. It pixelates before blurring, so the characters are gone rather than merely soft.

Read the full file on GitHub · 120 lines

Files

What ships with it

2 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.

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. 9d ago First seen · 120 lines · 57 tokens per session scan A 0f9c68648916

Subscribe to this mod's changes

device-screenshots is a skill published in the GitHub repository parawanderer/OpenTagViewer (379 stars, last pushed 2d ago), licensed MIT. It adds 57 tokens to every session and 1,229 once invoked, about $0.0003 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.

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