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 agentmods add skills/software-mansion/argent/argent-qa-flowsnpx skills add software-mansion/argent --skill argent-qa-flowsgit 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-qa-flows)<a href="https://agentmods.dev/skills/software-mansion/argent/argent-qa-flows"><img src="https://agentmods.dev/badge/skills/software-mansion/argent/argent-qa-flows.svg" alt="Measured on agentmods" 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 | $0.00127 | $0.02707 |
| Opus 5 | $0.00063 | $0.01354 |
| Sonnet 5 | $0.00025 | $0.00541 |
| Haiku 4.5 | $0.00013 | $0.00271 |
Grade A, and why
argent-qa-flows 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 yesterday.
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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create a QA regression flow
Load argent-create-flow as the authoring engine. Follow its required references for recorder syntax, selectors, polish, platform exceptions, and repair. This skill adds the QA contract and completion gate.
Vega supports every item below: launch: { vega: ... }, await:/assert: selectors, snapshot:, and idle all run there. Only the touch directives are missing, because Vega is remote-driven. Navigate with recorded tool: tv-remote steps and type with tool: keyboard, which leaves item 5 with nothing to govern. A D-pad path is relative to where focus already is, so gate every move with item 4's identity check rather than assuming the cursor landed. Read argent-tv-interact for focus reading and remote navigation.
Apple TV and Android TV are out of scope. The runner does not reject touch directives there, so they fail at the gesture layer instead of with authoring guidance. Use argent-tv-interact and report the limitation.
Physical iPhones run QA flows, with three hardware limits: replay never auto-binds a phone, so pass its udid as device (CLI --device) and keep it connected; pinch/rotate steps fail there like the live tools, so drive the app's own zoom UI instead; the flow tree is the describe tree (same ids and roles), so a selector authored on a simulator can miss there. Read argent-ios-device-interact for the app-scoped contract before recording.
Definition of done
A QA flow is complete only when:
- The first non-echo step is
launch:. In-flow setup proves a deterministic data baseline. Repeated runs do not accumulate artifacts or require manual cleanup. - The first walkthrough recorded every action and live structural check. Only the three documented polish insertions are unrecorded.
- Every requirement maps to a hard
await:,assert:, or reviewedsnapshot:. Echoes and screenshots are not verdicts. A negative check needs the same stable selector established as visible earlier. - Every screen change has destination identity followed by
idlereadiness. - Targets satisfy the stable-selector and coordinate-fallback rules. QA keeps coordinates only for genuinely unlabeled targets. Vacuous on Vega, which has no coordinate targets.
- The unchanged YAML passes twice with the same runner. Pass 1 starts with fresh mobile Argent services, and pass 2 follows immediately.
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.
- yesterday Changed · +2 lines b8c89207457d
- 6d ago First seen · 124 lines · 127 tokens per session scan A f2d518b7e793
argent-qa-flows is a skill published in the GitHub repository software-mansion/argent (2,378 stars, last pushed today), licensed Apache-2.0. It adds 127 tokens to every session and 2,707 once invoked, about $0.0006 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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