neurips

neurips is a skill for Claude Code from nanoAgentTeam/research-claw. It costs 42 tokens per session (2,627 once invoked), scanned A, original, MIT.

A formatting guide for papers submitted to NeurIPS, the Neural Information Processing Systems research conference. It covers the conference template and related paper-writing checks.

In plain words
What is it for?
Use it when preparing or fixing a NeurIPS submission. It helps select the appropriate template and apply guidance for writing, citations, reviews, and final checks.
Why use it?
It helps align a paper with the required layout, citation practices, reviewer expectations, and submission checks.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it when preparing or fixing a NeurIPS submission. It helps select the appropriate template and apply guidance for writing, citations, reviews, and final checks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nanoagentteam/research-claw/neurips
Install

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.

Any agent
npx skills add nanoAgentTeam/research-claw --skill neurips
Clone the repo
git clone --depth 1 https://github.com/nanoAgentTeam/research-claw

Made for: Claude Code.

Wrote 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.

agentmods badge for neurips

README.md
[![agentmods](https://agentmods.dev/badge/skills/nanoagentteam/research-claw/neurips.svg)](https://agentmods.dev/skills/nanoagentteam/research-claw/neurips)
Your own site
<a href="https://agentmods.dev/skills/nanoagentteam/research-claw/neurips"><img src="https://agentmods.dev/badge/skills/nanoagentteam/research-claw/neurips.svg" alt="Measured on agentmods" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,627 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00042 $0.02627
Opus 5 $0.00021 $0.01314
Sonnet 5 $0.00008 $0.00525
Haiku 4.5 $0.00004 $0.00263

Measured 8d ago against content hash 011c668812bc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

neurips 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.

config/.skills/neurips/SKILL.md · 242 lines

How it starts

The opening of the file, as written. The whole thing — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.

[SKILL: NeurIPS PAPER FORMAT]

Activate when: user mentions NeurIPS, Neural Information Processing Systems, or asks to use the NeurIPS template.

Execution Protocol

After this skill is activated, select the matching scenario based on user intent.

Shared Common Workflow

Before venue-specific template steps, also load and follow ml-paper-writing skill.

At minimum, apply these shared references:

  • writing-guide.md (narrative and clarity)
  • citation-workflow.md (verified citations; no hallucinations)
  • reviewer-guidelines.md (reviewer-facing quality checks)
  • checklists.md (pre-submission gates)

Built-in template: templates/neurips2025/ (referred to as TEMPLATES_DIR below), targeting NeurIPS 2025. Contents: neurips.sty, main.tex, extra_pkgs.tex, Makefile.

Pre-step: Year Confirmation & Template Acquisition

This step MUST be completed before any scenario below.

  1. Confirm the target year with the user (default: latest available year).
  2. Check whether TEMPLATES_DIR exists and includes required files: neurips.sty, main.tex, extra_pkgs.tex.
  3. Use local built-in template only when BOTH conditions hold:
    • target year = 2025
    • files in TEMPLATES_DIR are complete
  4. If either condition fails (target year is not 2025 OR local template files are missing/incomplete):
    • Inform the user local built-in template is unavailable or year-mismatched.
    • Guide the user to download the correct Author Kit from:
    • Unzip downloaded files directly into <PROJECT_CORE>.
    • All subsequent steps must use downloaded year-specific filenames.
  5. Filename substitution rule for all steps below:
    • Resolve the package name from the selected .sty filename (basename without .sty).
    • Treat neurips in commands/examples as a placeholder for that resolved package name.
    • Example: if the selected style file is neurips_2025.sty, replace neurips with neurips_2025 in \\usepackage, copy commands, and related checks.

Read the full file on GitHub · 242 lines

Files

What ships with it

4 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.

Changes

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.

  1. 8d ago First seen · 242 lines · 42 tokens per session scan A 011c668812bc

Subscribe to this mod's changes

neurips is a skill published in the GitHub repository nanoAgentTeam/research-claw (292 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 2,627 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.

Related

Other skills, from other repositories

neuroarxiv

Grounds a coding agent's architecture decisions in real arXiv prior art before it builds something new. Reads arXiv category-wise via real HTTP fetch, spawns parallel isolated reads across the papers found, scores/clusters them, then converges on ONE recommended path with citations, a first step, and known prior-art…

UditAkhourii/neuroarxiv · 162 tokens

research-expert

Expert-level research methodology, academic writing, statistical analysis, and scientific investigation. Use when the user mentions methodology, statistics, academic writing, or experimental design, or when the task involves Research Design, Statistical Analysis, or Data Analysis.

personamanagmentlayer/pcl · 50 tokens

arxiv-fetch

Fetch the latest arXiv papers and generate an on-demand digest. Use when the user asks to fetch/check today's (or the latest) arXiv papers, find new papers on a topic, or generate an ad-hoc arXiv digest. The agent judges relevance itself — no API keys needed.

yang3kc/daily_arxiv_digest · 66 tokens

ieee-acm-paper-writing

Draft, rewrite, compress, structure, calibrate, humanize, or audit engineering manuscripts for IEEE and ACM Transactions, journals, and conferences, with optional self-contained HTML audit maps. Use for abstracts, introductions, related work, system models, mathematical formulations, algorithms, experimental methods…

huguryildiz/ieee-acm-paper-writing · 151 tokens

paper-read

Read, analyze, and extract knowledge from academic papers. Handles PDFs and arXiv links. Produces structured summaries, identifies core contributions, evaluates methodology, and enables cross-paper comparison.

Calix-L/awesome-latex-skills · 40 tokens

overleaf

Sync and manage Overleaf LaTeX projects from the command line. Pull projects locally, push changes back, compile PDFs, and download compile outputs like .bbl files for arXiv submissions. Use when working with LaTeX, Overleaf, academic papers, or arXiv.

aloth/overleaf-skill · 62 tokens