Borrowing it
Nothing to install: this file belongs to vlad-ryzhkov/ai-context-engineering-for-qa. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/vlad-ryzhkov/ai-context-engineering-for-qa/main/.claude/skills/screenshot-analyze/SKILL.mdgit clone --depth 1 https://github.com/vlad-ryzhkov/ai-context-engineering-for-qaWrote 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/vlad-ryzhkov/ai-context-engineering-for-qa/screenshot-analyze)<a href="https://agentmods.dev/skills/vlad-ryzhkov/ai-context-engineering-for-qa/screenshot-analyze"><img src="https://agentmods.dev/badge/skills/vlad-ryzhkov/ai-context-engineering-for-qa/screenshot-analyze/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/vlad-ryzhkov/ai-context-engineering-for-qa/screenshot-analyze"><img src="https://agentmods.dev/badge/skills/vlad-ryzhkov/ai-context-engineering-for-qa/screenshot-analyze.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 | $0.00059 | $0.02345 |
| Opus 5 | $0.00030 | $0.01172 |
| Sonnet 5 | $0.00012 | $0.00469 |
| Haiku 4.5 | $0.00006 | $0.00234 |
Grade A, and why
screenshot-analyze 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 2d 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 — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
L10n & I18n UI Audit (Ride-Hailing)
Visual cross-localization UI analysis for ride-hailing applications.
Focus: Money, Time, Geolocation, RTL + TRANSLATION SEMANTICS.
Argument Parsing (MUST — Step 0)
Look for the screenshot path by priority — stop at the first match:
1. Skill args — any text after the command name. Examples:
/screenshot-analyze resources/screenshots/brazil_passenger_main_screen→resources/screenshots/brazil_passenger_main_screen/screenshot-analyze /abs/path/screens→/abs/path/screens
2. Glob search (fallback) — if args do not contain a path, run Glob("**/*.{png,jpg,jpeg,gif,webp}"), group by directories, pick the directory with the most images.
3. Ask the user — only if steps 1-2 yielded no result.
STRICTLY FORBIDDEN to ask about the path if steps 1-2 found a path or files.
Scope (What We Check)
1. SEMANTICS (Translation Quality) ← TOP PRIORITY
- Semantic errors (false friends, wrong context)
- Offensive/dangerous content
- Literal translation of compound words
2. LAYOUT
- Truncation, Overflow, Overlap
- RTL Mirroring
3. FORMATS (CLDR Compliance)
- Numbers, Currency, Date, Time, Distance
4. CONSISTENCY
- Single language, numeral system, terminology
Core Principles
1. Translation Verification FIRST
PRIMARY OBJECTIVE — VERIFY TRANSLATIONS FOR SEMANTIC ERRORS. Actively look for:
- False Friends — similar words with different meanings
- Wrong Context — correct word, wrong context
- Literal Translation — literal translation of idioms/terms
- Offensive Content — offensive/taboo content
2. Container vs Content
Besides translation, check: containers (does the text fit) and formats (CLDR). Do not nitpick style unless there is a semantic error.
3. RTL Mirroring
In RTL locales (ar, he, fa, ur) the entire UI is mirrored. Mirror: margins, navigation arrows, progress bars. DO NOT mirror: cars, maps.
4. Currency ≠ Locale
What ships with it
5 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.
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.
- 2d ago Changed · +297 lines · +36 tokens per session 74589ca1f1db
- 11d ago First seen · 21 lines · 23 tokens per session scan A f339c7d7ffbd
screenshot-analyze is a skill published in the GitHub repository vlad-ryzhkov/ai-context-engineering-for-qa (6 stars, last pushed 2d ago), licensed Unlicense. It adds 59 tokens to every session and 2,345 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 2026-08-31.
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