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.
git clone --depth 1 https://github.com/OXI-717/ai-native-toolkitWrote 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/commands/oxi-717/ai-native-toolkit/screencast)<a href="https://agentmods.dev/commands/oxi-717/ai-native-toolkit/screencast"><img src="https://agentmods.dev/badge/commands/oxi-717/ai-native-toolkit/screencast/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/commands/oxi-717/ai-native-toolkit/screencast"><img src="https://agentmods.dev/badge/commands/oxi-717/ai-native-toolkit/screencast.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 | $0.00035 | $0.00144 |
| Opus 5.5 | $0.00014 | $0.00058 |
| Sonnet 5.5 | $0.00007 | $0.00029 |
| Haiku 4.5 | $0.00003 | $0.00014 |
Grade A, and why
screencast 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 2mo 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.
What it actually says
Invoke the screencast skill to record a demo video of the flow described by: $ARGUMENTS
Follow the skill workflow: doctor/install guard → recon the flow via Playwright MCP → generate ./screencast/<name>-<date>/scenario.yaml → render with engine/make-video.sh → verify frames.
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.
- 2mo ago First seen · 10 lines · 35 tokens per session scan A 8759329fe497
screencast is a command published in the GitHub repository OXI-717/ai-native-toolkit (9 stars, last pushed 29d ago), licensed MIT. It adds 35 tokens to every session and 144 once invoked, about $0.0001 per session on Opus 5.5. 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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review-extension
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e2e
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