Borrowing it
Nothing to install: this file belongs to gaotiexinqu/OneResearchClaw. 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/gaotiexinqu/OneResearchClaw/main/.cursor/skills/remote-input/SKILL.mdgit clone --depth 1 https://github.com/gaotiexinqu/OneResearchClawWrote 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/gaotiexinqu/oneresearchclaw/remote-input)<a href="https://agentmods.dev/skills/gaotiexinqu/oneresearchclaw/remote-input"><img src="https://agentmods.dev/badge/skills/gaotiexinqu/oneresearchclaw/remote-input.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 167 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
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 | $0.00043 | $0.03271 |
| Opus 5 | $0.00022 | $0.01636 |
| Sonnet 5 | $0.00009 | $0.00654 |
| Haiku 4.5 | $0.00004 | $0.00327 |
Grade A, and why
remote-input 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 — 395 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Remote Input
Download remote content (arxiv papers, YouTube videos, Bilibili videos) to local storage and seamlessly integrate into the downstream pipeline.
What This Skill Does
This skill acts as a pre-processing layer for the pipeline:
- Detects URL type (arxiv, YouTube, or Bilibili)
- Downloads content to
data/raw_inputs/remote/ - Returns the local file path
- Triggers the next pipeline stage
Supported URL Types
| URL Type | Download Target | Local Extension | Downstream Routing |
|---|---|---|---|
https://arxiv.org/abs/... |
.pdf |
document-grounding |
|
https://arxiv.org/pdf/... |
.pdf |
document-grounding |
|
https://www.youtube.com/watch?v=... |
Video | .mp4/.mkv |
meeting-video-grounding |
https://youtu.be/... |
Video | .mp4/.mkv |
meeting-video-grounding |
https://www.youtube.com/shorts/... |
Video | .mp4/.mkv |
meeting-video-grounding |
https://bilibili.com/video/BV... |
Video | .mp4/.mkv |
meeting-video-grounding |
https://www.bilibili.com/video/av... |
Video | .mp4/.mkv |
meeting-video-grounding |
https://b23.tv/... |
Video | .mp4/.mkv |
meeting-video-grounding |
Note on merge failure: When video download produces separate video and audio files (merge failure), the downloader returns
merge_failed: truewithaudio_pathpointing to the audio file. The downstream routing switches tomeeting-audio-groundinginstead ofmeeting-video-grounding.
Directory Structure
data/raw_inputs/remote/
├── arxiv/
│ └── <paper_id>.pdf # e.g., 2301.07041.pdf
├── youtube/
│ └── <video_title>.mp4 # e.g., "Introduction to Transformers.mp4"
├── bilibili/
│ └── <video_title>.mp4 # e.g., "教程视频.mp4"
└── metadata/
└── <ground_id>.json # Download metadata
Workflow
Step 1. Parse Input URL
Detect the URL type:
If URL contains "arxiv.org":
→ Use arxiv downloader
→ Ground ID = arxiv paper ID (e.g., "2301.07041")
If URL contains "youtube.com" or "youtu.be":
→ Use YouTube downloader
→ Ground ID = sanitized video title or video ID
If URL contains "bilibili.com" or "b23.tv":
→ Use Bilibili downloader
→ Ground ID = BV ID (e.g., "BV1xx411c7JZ")
What ships with it
2 files 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.
- 8d ago First seen · 395 lines · 43 tokens per session scan A a101c8aa21b1
remote-input is a skill published in the GitHub repository gaotiexinqu/OneResearchClaw (445 stars, last pushed 4mo ago), licensed MIT. It adds 43 tokens to every session and 3,271 once invoked, about $0.0002 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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