novelty-check

novelty-check is a skill for Claude Code from AutoConference/AutoConference-skill. It costs 49 tokens per session (1,185 once invoked), scanned A, original, Apache-2.0.

A literature-search workflow that checks whether a proposed research idea or method is new by examining recent papers and preprints. It breaks the idea into technical claims and looks for work that overlaps with each one.

In plain words
What is it for?
Use it before implementation or submission to search recent research, compare overlapping methods, and assess which parts of an idea may be original.
Why use it?
It reduces the risk of implementing or presenting an idea that has already been published, or of making novelty claims without checking relevant evidence.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions Codex.

Good fit Use it before implementation or submission to search recent research, compare overlapping methods, and assess which parts of an idea may be original.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/autoconference/autoconference-skill/novelty-check
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 AutoConference/AutoConference-skill --skill novelty-check
Clone the repo
git clone --depth 1 https://github.com/AutoConference/AutoConference-skill

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 novelty-check

README.md
[![agentmods](https://agentmods.dev/badge/skills/autoconference/autoconference-skill/novelty-check/github.svg)](https://agentmods.dev/skills/autoconference/autoconference-skill/novelty-check)
Your own site
<a href="https://agentmods.dev/skills/autoconference/autoconference-skill/novelty-check"><img src="https://agentmods.dev/badge/skills/autoconference/autoconference-skill/novelty-check/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.

agentmods 80×15 button for novelty-check

Your own site · 80×15
<a href="https://agentmods.dev/skills/autoconference/autoconference-skill/novelty-check"><img src="https://agentmods.dev/badge/skills/autoconference/autoconference-skill/novelty-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,185 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.
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 $0.00049 $0.01185
Opus 5.5 $0.00020 $0.00474
Sonnet 5 $0.00010 $0.00237
Haiku 4.5 $0.00005 $0.00119

Measured 3d ago against content hash c512579faa06, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-28, from the pricing page.

Security

Grade A, and why

novelty-check 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 3d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/aris/novelty-check/SKILL.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Novelty Check Skill

Check whether a proposed method/idea has already been done in the literature: $ARGUMENTS

Constants

  • REVIEWER_MODEL = gpt-5.6-sol — Model used via Codex MCP. Must be an OpenAI model (e.g., gpt-5.6-sol, o3, gpt-4o)

Instructions

Given a method description, systematically verify its novelty:

Phase A: Extract Key Claims

  1. Read the user's method description
  2. Identify 3-5 core technical claims that would need to be novel:
    • What is the method?
    • What problem does it solve?
    • What is the mechanism?
    • What makes it different from obvious baselines?

Phase B: Multi-Source Literature Search

For EACH core claim, search using ALL available sources:

  1. Web Search (via WebSearch):

    • Search arXiv, Google Scholar, Semantic Scholar
    • Use specific technical terms from the claim
    • Try at least 3 different query formulations per claim
    • Include year filters for 2024-2026
  2. Known paper databases: Check against:

    • ICLR 2025/2026, NeurIPS 2025, ICML 2025/2026
    • Recent arXiv preprints (2025-2026)
  3. Read abstracts: For each potentially overlapping paper, WebFetch its abstract and related work section

Phase C: Cross-Model Verification

Call REVIEWER_MODEL via Codex MCP (mcp__codex__codex) with xhigh reasoning. When the method description plus the Phase-B paper list is more than a short note, avoid pasting it inline into the MCP prompt. Write a dossier file such as NOVELTY_DOSSIER.md (or a project-local equivalent) containing the method description, core claims, candidate papers, and the exact questions below, then send only the file path:

mcp__codex__codex:
  model: gpt-5.6-sol
  config: {"model_reasoning_effort": "xhigh"}
  prompt: |
    Read the novelty dossier at <absolute path to NOVELTY_DOSSIER.md> and
    follow all instructions in it.

Dossier contents should include:

  • The proposed method description
  • All papers found in Phase B
  • Ask: "Is this method novel? What is the closest prior work? What is the delta?"

Read the full file on GitHub · 102 lines

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. 3d ago First seen · 102 lines · 49 tokens per session scan A c512579faa06

Subscribe to this mod's changes

novelty-check is a skill published in the GitHub repository AutoConference/AutoConference-skill (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 49 tokens to every session and 1,185 once invoked, about $0.0002 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 2026-09-25.

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