Audit GitHub Actions that run AI agents for prompt injection, unsafe interpolation, sandbox gaps, and permissive actor rules. Use for agentic CI workflows, not general application code review.
日本語の概要は準備中です。原文の説明を表示しています。
Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Publish, manage, and link research papers on the Hugging Face Hub — arXiv indexing, model/dataset linking, authorship management, and professional markdown research-article generation.
Paper Pages (index/discover), arXiv integration (auto-indexing from arXiv IDs), model/dataset linking via metadata, authorship verification, and a research-article template.
The included scripts/paper_manager.py uses PEP 723 inline dependencies — prefer uv run over manual environment setup. Requires HF_TOKEN (write access) in the environment. All paths in the commands below are relative to this skill's directory — cd there first, or use the full path.
Index a paper from arXiv (or visit https://huggingface.co/papers/{arxiv-id} directly):
uv run scripts/paper_manager.py index --arxiv-id "2301.12345"
uv run scripts/paper_manager.py check --arxiv-id "2301.12345" # check if already indexed
Link a paper to a model/dataset/space — the Hub extracts the arXiv ID and adds an arxiv:<PAPER_ID> tag, making the repo discoverable from the Paper Page:
uv run scripts/paper_manager.py link \
--repo-id "username/repo-name" --repo-type "model|dataset|space" \
--arxiv-id "2301.12345" [--arxiv-ids "id1,id2,id3"] \
[--citation "Full citation text"] [--create-pr]
Claim authorship (or manually: visit the paper page, click your name, "Claim authorship", await admin verification):
uv run scripts/paper_manager.py claim --arxiv-id "2301.12345" --email "your.email@institution.edu"
uv run scripts/paper_manager.py check-authorship --arxiv-id "2301.12345"
Manage profile visibility (or via account settings → Papers):
uv run scripts/paper_manager.py list-my-papers
uv run scripts/paper_manager.py toggle-visibility --arxiv-id "2301.12345" --show true|false
Create a research article from a template (standard — traditional structure; modern — Distill-inspired, dynamic TOC, responsive; arxiv — arXiv-style; ml-report — ML experiment report):
uv run scripts/paper_manager.py create \
--template "standard|modern|arxiv|ml-report" --title "Paper Title" \
[--authors "Author1, Author2"] [--abstract "Abstract text"] [--output "paper.md"]
uv run scripts/paper_manager.py convert --input "paper.md" --output "paper.html" [--style "modern|classic"]
Search, inspect, validate:
uv run scripts/paper_manager.py search --query "transformer attention"
uv run scripts/paper_manager.py info --arxiv-id "2301.12345" --format "json"
uv run scripts/paper_manager.py citation --arxiv-id "2301.12345" --format "bibtex"
uv run scripts/paper_manager.py validate --repo-id "username/model-name" --repo-type "model"
---
title: Your Paper Title
authors: Jane Doe, John Smith
affiliations: University X, Lab Y
date: 2025-01-15
arxiv: 2301.12345
tags: [machine-learning, nlp, fine-tuning]
---
# Abstract
# 1. Introduction
# 2. Related Work
# 3. Methodology
# 4. Experiments
# 5. Results
# 6. Discussion
# 7. Conclusion
# References
The modern template adds a dynamic table of contents, responsive layout, code highlighting, interactive figures, LaTeX math, and citation/author-affiliation linking.
Model and dataset cards need proper frontmatter for the Hub to extract the arXiv tag correctly:
---
language: [en]
license: apache-2.0
tags: [text-generation, transformers, llm]
library_name: transformers
---
Followed by a # Model Name section referencing [Our Paper](https://arxiv.org/abs/2301.12345) and a ## Citation section with a fenced bibtex block containing the standard @article{...} entry (author, title, journal, year).
Dataset cards follow the same pattern with task_categories/size_categories instead of library_name.
Publish new research: create the article -> submit to arXiv externally -> index -> link to the model -> claim authorship.
Link an existing paper to multiple repos: check -> index if needed -> link once per model/dataset/space repo-id.
Update a model with a paper reference: hf download user/model README.md -> link with --citation — the script adds YAML metadata if missing, inserts the arXiv link, adds the formatted citation, and preserves existing content.
Batch-link multiple papers to one repo:
for arxiv_id in "2301.12345" "2302.67890"; do
uv run scripts/paper_manager.py link --repo-id "username/model-name" --repo-type "model" --arxiv-id "$arxiv_id"
done
Index papers as soon as published; keep citations consistent across related repos. Add YAML frontmatter with correct license and task tags to every card. Claim authorship with an institutional email and keep visibility settings current. Link papers to every relevant model/dataset/Space, with BibTeX citations. Use one template consistently within a project, and include code/data links.
hf.co/papers/{arxiv-id} to trigger indexing.HF_TOKEN lacks write access to the repository.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Audit GitHub Actions that run AI agents for prompt injection, unsafe interpolation, sandbox gaps, and permissive actor rules. Use for agentic CI workflows, not general application code review.
日本語の概要は準備中です。原文の説明を表示しています。
Audit and improve project-rules files (AGENTS.md, CLAUDE.md, .agents/instructions, local overrides) so the agent keeps accurate project context. Use when the user asks to check, audit, review, update, improve, or fix their AGENTS.md or CLAUDE.md, mentions "project rules maintenance" or "agent context optimization", or when the codebase has changed enough that the rules file may be stale. Scans the repository for every rules file, grades each against a quality rubric, outputs a quality report, and applies targeted edits only after user approval.
日本語の概要は準備中です。原文の説明を表示しています。
Capture learnings from the current session into the project-rules file (AGENTS.md, CLAUDE.md, or local override) so future sessions benefit. Use when the user says "revise the rules", "update AGENTS.md / CLAUDE.md with what we just learned", "save this to project memory", "remember this for next time", or at the end of a productive session when valuable context has emerged that is not yet documented. This complements agents-md-improver — improver audits, while this one captures.
日本語の概要は準備中です。原文の説明を表示しています。
Operational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design. Use as the reference rubric when building or reviewing marketing sites, product interfaces, dashboards, portfolios, or e-commerce pages, especially alongside frontend-design.
日本語の概要は準備中です。原文の説明を表示しています。
Design a feature architecture by analyzing existing codebase patterns and conventions, then provide a comprehensive implementation blueprint with specific files to create or modify, component designs, data flows, and a build sequence. Use this skill when the user asks for an architecture design, an implementation plan for a non-trivial feature, or when dispatched as a sub-task during feature-dev architecture phase.
日本語の概要は準備中です。原文の説明を表示しています。
Deeply analyze an existing codebase feature by tracing execution paths, mapping architecture layers, understanding patterns and abstractions, and documenting dependencies. Use this skill when you need to understand how a feature works before modifying or extending it, when dispatched as a sub-task during feature-dev exploration, or when the user asks "how does X work in this codebase".
日本語の概要は準備中です。原文の説明を表示しています。