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nature-paper-to-patent

nature-paper-to-patent is a skill for Claude Code from YuanyuanMa03/academic-research-skills. It costs 102 tokens per session (804 once invoked), scanned A, original, MIT.

A drafting workflow that converts papers, theses, reports, source code, figures, or research manuscripts into evidence-based Chinese invention-patent drafts. It records where each claimed technical feature comes from and excludes unsupported features from formal claims.

In plain words
What is it for?
It helps prepare patent drafts, claim sets, disclosure analyses, and paper-to-patent audits for software, algorithms, devices, systems, processes, and materials.
Why use it?
It reduces the risk of turning a research contribution into claims that the source does not support. It also keeps the patent draft traceable to text, equations, figures, and code evidence.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the nature-paper-to-patent plugin — 1 skill shipped together

not rated 75repo today A scan 102 tokens original MIT

Good fit It helps prepare patent drafts, claim sets, disclosure analyses, and paper-to-patent audits for software, algorithms, devices, systems, processes, and materials.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yuanyuanma03/academic-research-skills/nature-paper-to-patent
View source ↗ YuanyuanMa03/academic-research-skills
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 YuanyuanMa03/academic-research-skills --skill nature-paper-to-patent
Clone the repo
git clone --depth 1 https://github.com/YuanyuanMa03/academic-research-skills

Made for: Claude Code.

Or install nature-paper-to-patent, the plugin that ships this one along with the rest of its 1 skill.

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 nature-paper-to-patent

README.md
[![agentmods](https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/nature-paper-to-patent/github.svg)](https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/nature-paper-to-patent)
Your own site
<a href="https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/nature-paper-to-patent"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/nature-paper-to-patent/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 nature-paper-to-patent

Your own site · 80×15
<a href="https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/nature-paper-to-patent"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/nature-paper-to-patent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 804 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 $0.00102 $0.00804
Opus 5.5 $0.00041 $0.00322
Sonnet 5.5 $0.00020 $0.00161
Haiku 4.5 $0.00010 $0.00080

Measured today against content hash 5a35bc54d90f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

nature-paper-to-patent 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 today.

The scan reads SKILL.md. This mod also ships 9 executable files (scripts/audit_claims.py, scripts/build_patent_package.py, scripts/extract_pdf_text.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugins/nature-paper-to-patent/skills/nature-paper-to-patent/SKILL.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Paper to Chinese Patent

Use this file as the router for the patent-drafting workflow. Do not draft the application directly from the paper abstract or contribution list.

1. Load the workflow

Read manifest.yaml, then read every file under always_load.

Detect these axes from the user's files and request:

  • source_format: selectable PDF, scanned PDF, pasted text, or mixed project;
  • task_mode: full draft, claim set, disclosure analysis, or paper-patent audit;
  • invention_type: algorithm/software, apparatus/system, process/material, or mixed.

State the detected values in one short line. Load only the matching fragments declared in the manifest. Load detailed references only when their condition applies.

2. Preserve source grounding

Create stable source IDs before drafting:

  • P001... for paper text blocks;
  • E001... for equations;
  • F001... for source figures;
  • C001... for source-code or supplementary evidence.

Every material feature in a formal claim must map to one or more source IDs. Use only explicit, inherent, needs-confirmation, or unsupported as support states. Exclude unsupported features from formal claims.

Never infer inventorship, ownership, unpublished implementation details, publication dates, prior-art conclusions, or legal sufficiency. Use [TO CONFIRM: specific question] outside formal claims when facts are missing.

3. Draft through stage gates

Complete the stages in static/core/workflow.md in order. Persist the intermediate artifacts specified there. Do not move to formal claims until the source map, terminology ledger, inventories, evidence ledger, and invention concept pass their gates.

For a full application, draft claims first, then align the specification, figures, embodiments, and abstract to the claim terminology and step order.

4. Produce Chinese formal documents

Agent-facing analysis may use the user's preferred language. Produce formal Chinese patent deliverables in Chinese:

  • 权利要求书;
  • 说明书;
  • 说明书摘要;
  • 摘要附图;
  • figure labels and descriptions.

Read the full file on GitHub · 89 lines

Files

What ships with it

33 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. today First seen · 89 lines · 102 tokens per session scan A 5a35bc54d90f

Subscribe to this mod's changes

nature-paper-to-patent is a skill published in the GitHub repository YuanyuanMa03/academic-research-skills (75 stars, last pushed today), licensed MIT. It adds 102 tokens to every session and 804 once invoked, about $0.0004 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 2026-10-29.

Legal and complianceScientificcnkicodexgooglegoogle-scholarpaper
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