Borrowing it
Nothing to install: this file belongs to RipeMangoBox/BITE. 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/RipeMangoBox/BITE/main/.claude/skills/papers-collect-from-github-repo/SKILL.mdgit clone --depth 1 https://github.com/RipeMangoBox/BITEWrote 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/ripemangobox/bite/papers-collect-from-github-repo)<a href="https://agentmods.dev/skills/ripemangobox/bite/papers-collect-from-github-repo"><img src="https://agentmods.dev/badge/skills/ripemangobox/bite/papers-collect-from-github-repo.svg" alt="Measured on agentmods" height="20"></a>- 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 | $0.00090 | $0.01787 |
| Opus 5 | $0.00045 | $0.00894 |
| Sonnet 5 | $0.00018 | $0.00357 |
| Haiku 4.5 | $0.00009 | $0.00179 |
Grade A, and why
papers-collect-from-github-repo 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Papers Collect From GitHub Repo
Purpose
Extract paper candidates from any GitHub repository and output rows aligned with obsidian-vault/paper_list.csv.
Supported repo types (non-exhaustive):
| Type | Example |
|---|---|
| Awesome / curated list | Foruck/Awesome-Human-Motion |
| Survey companion repo | ChenHsing/Awesome-Video-Diffusion-Models (CSUR) |
| Lab / group paper list | showlab/showlab.github.io |
| Conference accepted papers | ICLR/ICLR-2026-accepted-papers |
| Benchmark / leaderboard repo | open-compass/opencompass |
| Topic-specific collection | soraproducer/Awesome-Human-Interaction-Motion-Generation |
| Any repo with a structured paper list in README or docs | — |
Because repo formats vary widely (Markdown tables, bullet lists, mixed HTML, nested docs, multiple files, etc.), this skill does not include fixed scripts. The agent writes one-off parsing logic for each target.
Input
User provides:
- GitHub repo URL: e.g.
https://github.com/Foruck/Awesome-Human-Motion - target file (optional): defaults to
README.md; can be a specific path likedocs/papers.mdor a directory to scan - include/exclude keywords (optional): e.g. include
motion generation, excludesurvey - target category (optional): e.g.
Motion_Generation_Text_Speech_Music_Driven - venue/year hint (optional): e.g.
CVPR 2025— used as default when venue cannot be parsed
Output Format
Output must align with the column format of obsidian-vault/paper_list.csv:
state,importance,paper_title,venue,project_link_or_github_link,paper_link,sort,pdf_path
Field notes:
| Column | Initial default | Description |
|---|---|---|
| state | Wait |
Later can be changed manually to Skip, or remain Wait for download |
| importance | empty | Later manually labeled as S/A/B/C |
| paper_title | parsed from repo | paper title |
| venue | parsed from repo, fallback Unknown |
e.g., CVPR 2025, ICLR 2026; if only on open platforms, use arXiv YYYY |
| project_link_or_github_link | project page or GitHub link | prefer project page; if confirmed no open source, use N/A |
| paper_link | arXiv / OpenReview link | prefer arXiv abs link |
| sort | section/category heading in source | join words with _, e.g. Motion_Generation |
| pdf_path | empty | filled later by papers-download-from-list |
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.
- 8d ago First seen · 149 lines · 90 tokens per session scan A 469e41c5b785
papers-collect-from-github-repo is a skill published in the GitHub repository RipeMangoBox/BITE (61 stars, last pushed 25d ago), licensed MIT. It adds 90 tokens to every session and 1,787 once invoked, about $0.0005 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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