Borrowing it
Nothing to install: this file belongs to mnvsk97/eyeroll. 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/mnvsk97/eyeroll/main/AGENTS.mdgit clone --depth 1 https://github.com/mnvsk97/eyerollWrote 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/instructions/mnvsk97/eyeroll/agents-md)<a href="https://agentmods.dev/instructions/mnvsk97/eyeroll/agents-md"><img src="https://agentmods.dev/badge/instructions/mnvsk97/eyeroll/agents-md/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/instructions/mnvsk97/eyeroll/agents-md"><img src="https://agentmods.dev/badge/instructions/mnvsk97/eyeroll/agents-md.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 | $0.00706 | $0.00706 |
| Opus 5.5 | $0.00282 | $0.00282 |
| Sonnet 5.5 | $0.00141 | $0.00141 |
| Haiku 4.5 | $0.00071 | $0.00071 |
Grade A, and why
eyeroll AGENTS.md 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 1mo 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Project
eyeroll — AI eyes that roll through video footage. Takes video URLs (Loom, YouTube), local video files, or screenshots as input. Supports Gemini Flash (API) and Ollama with Qwen3-VL (local, private). Produces structured notes that coding agents can act on — fix bugs, build features, create skills, or anything else.
Commands
# Install
pip install .
# or with uv:
uv sync
# Run tests
pytest
pytest --cov --cov-report=term-missing
# CLI
eyeroll init # set up Gemini API key
eyeroll watch <url-or-path> # analyze (gemini default)
eyeroll watch <url> --context "broken after PR #432" # with context
eyeroll watch <path> --backend ollama # use local Qwen3-VL
eyeroll watch <path> -b ollama -m qwen3-vl:2b # specific model
eyeroll watch <path> --verbose --output report.md # verbose + write to file
Architecture
- Pipeline:
acquire.py→extract.py→analyze.py→watch.py(orchestrator) - backend.py: Abstract Backend class with GeminiBackend and OllamaBackend implementations. Factory via
get_backend(). - acquire.py: Downloads from URLs via yt-dlp, resolves local files. Returns file_path, media_type, title.
- extract.py: ffmpeg wrappers for key frame extraction, audio extraction, duration detection.
- analyze.py: Backend-agnostic analysis. Frame-by-frame with structured prompts, direct video upload (Gemini only), audio transcription, and synthesis.
- watch.py: Orchestrates the pipeline. Chooses strategy based on backend capabilities and video size.
- cli.py: Click CLI with
initandwatchcommands.--backendand--modelflags.
Backends
- gemini (default): Gemini Flash API. Supports direct video upload, audio transcription. Requires GEMINI_API_KEY.
- openai: OpenAI GPT-4o. Frame-by-frame image analysis + Whisper audio transcription. Requires OPENAI_API_KEY.
- ollama: Local models via Ollama. Supports frame-by-frame image analysis only (no direct video, no audio). Default model: qwen3-vl. No API key needed.
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.
- 1mo ago First seen · 56 lines · 706 tokens per session scan A 97b9bba53d83
eyeroll AGENTS.md is an instructions file published in the GitHub repository mnvsk97/eyeroll (19 stars, last pushed 5mo ago), licensed MIT. It adds 706 tokens to every session, about $0.0028 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 2026-08-30.
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