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 skills add qiannianhuanxiang/DSHA --skill screen-ocr-operatorgit clone --depth 1 https://github.com/qiannianhuanxiang/DSHAWrote 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/qiannianhuanxiang/dsha/screen-ocr-operator)<a href="https://agentmods.dev/skills/qiannianhuanxiang/dsha/screen-ocr-operator"><img src="https://agentmods.dev/badge/skills/qiannianhuanxiang/dsha/screen-ocr-operator/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/qiannianhuanxiang/dsha/screen-ocr-operator"><img src="https://agentmods.dev/badge/skills/qiannianhuanxiang/dsha/screen-ocr-operator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.01121 |
| Opus 5 | $0.00000 | $0.00561 |
| Sonnet 5 | $0.00000 | $0.00224 |
| Haiku 4.5 | $0.00000 | $0.00112 |
Grade A, and why
screen-ocr-operator 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 12d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Screen OCR Operator (Commander Mode)
Act as the commander: you issue ADB commands, the vision model looks at screenshots and returns a concrete operation plan. The goal is to finish screen tasks with the fewest possible screenshot/OCR round-trips.
Roles
- Commander (you): capture screenshots, call the vision model, execute ADB taps/input, verify.
- Eyes (vision model): OCR the screen, identify UI elements, return coordinates and steps.
- Hands (ADB):
input tap,input text,input keyevent,am start, etc.
Key optimization rules
- Ask the model for a complete plan, not a single action.
- Give the model the task + current screenshot.
- Ask it to return a JSON list of actions with coordinates:
{ "actions": [ {"type": "tap", "x": 630, "y": 1090}, {"type": "text", "value": "hello"}, {"type": "key", "key": "ENTER"} ], "verify": "expected screen after actions" }
- One model call per meaningful milestone.
- Don't screenshot + OCR after every tap.
- Only re-ask when the next step depends on a changed screen or after a risky action.
- Use Android APIs for deterministic checks first.
dumpsys window | grep mCurrentFocus→ which app is foreground.dumpsys input_method | grep mInputShown→ is keyboard open.uiautomator dump→ native UI nodes/bounds when available.- These are faster and more reliable than OCR for state checks.
- Shrink screenshots before sending to the model.
- Capture full screen, then downscale to max width ~720px and save as JPEG quality ~80.
- Smaller payload = much faster API round-trip.
- Batch ADB commands.
- Combine independent shell commands into one
adb shellinvocation. - Keep sleeps short (
sleep 0.5–1) and only wait when the UI actually needs time.
- Combine independent shell commands into one
- Verify at the end (or at major checkpoints).
- Final screenshot + one model confirmation is usually enough.
- For long tasks, verify after each phase, not after every tap.
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.
- 12d ago First seen · 103 lines · 0 tokens per session scan A 8cec4cabad81
screen-ocr-operator is a skill published in the GitHub repository qiannianhuanxiang/DSHA (392 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,121 tokens. 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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