AIRI is a self-hosted virtual AI companion that gives an AI character a voice, visual presence, memory, and the ability to interact with games and coding activity. People use it as a personal digital companion on the web, macOS, or Windows, including for voice chat and gameplay. The catalogue add-ons provide workflows for working with the AIRI project.
Borrowing it
Nothing to install: this file belongs to moeru-ai/airi. 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/moeru-ai/airi/main/.agents/skills/use-vishot/SKILL.mdgit clone --depth 1 https://github.com/moeru-ai/airiWrote 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/moeru-ai/airi/use-vishot)<a href="https://agentmods.dev/skills/moeru-ai/airi/use-vishot"><img src="https://agentmods.dev/badge/skills/moeru-ai/airi/use-vishot/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/moeru-ai/airi/use-vishot"><img src="https://agentmods.dev/badge/skills/moeru-ai/airi/use-vishot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00055 | $0.00683 |
| Opus 5 | $0.00028 | $0.00342 |
| Sonnet 5 | $0.00011 | $0.00137 |
| Haiku 4.5 | $0.00006 | $0.00068 |
Grade A, and why
use-vishot 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 11d 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 — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use Vishot
Use Vishot as the common screenshot interface and delegate runtime-specific behavior to the matching variant skill.
Workflow
- Identify every requested surface and state: route or window, viewport, theme, locale, fixture data, and any interaction needed to reach it.
- Reuse product-owned Vishot scenarios, stories, routes, and stable selectors before creating temporary automation.
- If the existing scenarios do not expose a valid reusable helper for the requested state, write the smallest disposable scenario or helper needed to reach it. Keep this automation outside tracked scenario directories unless the user separately asks to productize it. Run the complete startup, state preparation, capture, and artifact-inspection flow; do not stop after documenting that a helper is missing.
- Select the runtime variant:
- Invoke
$use-vishot-with-electronfor Electron windows. - Invoke
$use-vishot-with-webfor browser routes. - Invoke
$use-vishot-with-capacitorfor Capacitor WebView or native-shell evidence. - Also invoke
$use-vishot-with-input-filewhen reaching the requested state requires a local file chooser or file input.
- Invoke
- When developing or debugging the disposable automation, use a locally available
$agent-browserto inspect web or Capacitor DOM and interaction paths. For Electron window discovery and interaction, also invoke$agent-browser-electron. Use these skills as development and validation aids; do not make their availability a prerequisite for Vishot capture. - Produce the final screenshot artifacts with Vishot whenever possible, even when agent-browser helped discover selectors or verify the interaction sequence. Treat a missing product helper as temporary automation work, not as proof that Vishot cannot capture the state; report a Vishot limitation only after reproducing a concrete runtime failure.
- Give the variant an explicit output directory. Directory ownership belongs to the caller; Vishot only writes named capture artifacts into that directory.
- Keep locale, theme, data, viewport, and readiness conditions deterministic when captures will be compared.
- Inspect every generated image. Reject blank, loading, error, permission, onboarding, or unstable frames unless that is the requested state.
- Return a manifest rather than relying on directory order:
What ships with it
1 file 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.
- 11d ago First seen · 43 lines · 55 tokens per session scan A b097281c5e5b
use-vishot is a skill published in the GitHub repository moeru-ai/airi (49,010 stars, last pushed today), licensed MIT. It adds 55 tokens to every session and 683 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.
Other skills, from other repositories
claude_code
This document describes how a Claude Code agent (or any agent using the Claude Code CLI pattern) invokes the Seiðr-Smiðja forge through the Rúnstafr CLI bridge.
web-fetch
Fetch and extract readable content from web pages. Use for lightweight page access without browser automation.
debug-optimize-lcp
Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…
pinchtab-mcp
Use this skill when a task requires browser automation through PinchTab's MCP server connected to a remote browser instance. Covers navigation, element interaction, data extraction, form filling, multi-step flows, and session management via MCP tools.
azure-messaging-webpubsub-java
Build real-time web applications with Azure Web PubSub SDK for Java. Use when implementing WebSocket-based messaging, live updates, chat applications, or server-to-client push notifications.
google-safe-browsing
Prevent and fix Google Safe Browsing "Dangerous site" flags. Use when launching a public web app, buying/picking a domain, building a login or signup page, or when any site shows a red "Dangerous site" / "Deceptive site" warning in Chrome, Brave, Safari, Firefox, or Edge. Triggers on "dangerous site", "deceptive…