Argent is a toolkit that lets an AI assistant control and inspect iOS, Android, TV, Electron, and Chromium applications through simulators, emulators, physical devices, or desktop connections. It is for developers who want an agent to interact with interfaces, reproduce issues, test features, debug applications, or run profiling tasks. The catalogue add-ons expose Argent's device-control and development workflows to coding agents.
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 software-mansion/argent --skill argent-screen-recordinggit clone --depth 1 https://github.com/software-mansion/argentWrote 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/software-mansion/argent/argent-screen-recording)<a href="https://agentmods.dev/skills/software-mansion/argent/argent-screen-recording"><img src="https://agentmods.dev/badge/skills/software-mansion/argent/argent-screen-recording.svg" alt="Measured on agentmods" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00059 | $0.01827 |
| Opus 5 | $0.00030 | $0.00914 |
| Sonnet 5 | $0.00012 | $0.00365 |
| Haiku 4.5 | $0.00006 | $0.00183 |
Grade A, and why
argent-screen-recording 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 8d 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
1. Tools
screen-recording-start— start capturing the screen of a booted device to a video file. Frames come from the same simulator-server backend thatscreenshotand the interaction tools already use, and are encoded live to h264 mp4 (constant 30 fps, device-native resolution).screen-recording-stop— stop the capture, finalize the container, and retrieve the video as a downloadable artifact (video.hostPathfor co-located clients).
One recording per device at a time; different devices can record concurrently. Recording does not disturb anything else reading the device — a preview window can stay open on the same screen.
2. Critical: never leave a recording running
A recording does not stop itself before its timeLimitSeconds cap, so a forgotten one keeps capturing until the cap fires — holding the recording session, wasting disk, and delaying the video you are waiting on (and with trimStatic: false it comes back padded with dead air). Two safety nets exist — use both:
- Set yourself a reminder the moment the recording starts. You know the expected capture length (the interaction you are about to drive). Immediately after
screen-recording-startreturns, schedule a wake-up for that expected end time using whatever your harness provides — a built-in reminder/wakeup or scheduled-task tool if you have one, otherwise a background shell runningsleep <expected-seconds>whose completion notification pulls you back. When it fires, callscreen-recording-stop. Do not rely on remembering. - Read the tool-result notes. While a recording is running, every argent tool result carries a
NOTE:reminding you it is still going and how to stop it. If the note says the recording already ended (time limit hit), still callscreen-recording-stop— that is what hands you the file.
3. Workflow
- Ensure the target device is booted and the app is in the state you want the video to open on (
list-devices,launch-app,argent-device-interact). - Call
screen-recording-startwithudidand atimeLimitSecondsslightly above the expected interaction length (default 180, max 600). Taps and swipes are drawn into the video by default (see the touch-visualizer note below); passshowTouches: falsefor a clean raw-screen capture. - Set the end-of-recording reminder described in §2 — this step is not optional.
- Drive the interaction to capture: gestures, navigation, typing (
argent-device-interact). Preferrun-sequencefor tight multi-step interactions so tool-call latency does not pad the video. - Call
screen-recording-stopwith the sameudid. It returns{ video, durationMs, wallClockMs?, trimmedMs?, warning? };videois an artifact whose resolved path points at the durably-saved file (see below). The video is already final when stop returns (the watermark is stamped during capture, not in a second pass), so stop takes well under a second. - Check
warning: it reports cap-triggered stops, early encoder exits, a dropped frame stream, and possibly-truncated containers. Verify the file plays (or at least has a sane size) before presenting it to the user.
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.
- 8d ago First seen · 49 lines · 59 tokens per session scan A de5fa6e20ae8
argent-screen-recording is a skill published in the GitHub repository software-mansion/argent (2,388 stars, last pushed today), licensed Apache-2.0. It adds 59 tokens to every session and 1,827 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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