Borrowing it
Nothing to install: this file belongs to 7toCR/paper2patent. 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/7toCR/paper2patent/main/.claude/skills/paper2patent/SKILL.mdgit clone --depth 1 https://github.com/7toCR/paper2patentWrote 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/7tocr/paper2patent/paper2patent)<a href="https://agentmods.dev/skills/7tocr/paper2patent/paper2patent"><img src="https://agentmods.dev/badge/skills/7tocr/paper2patent/paper2patent/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.
<a href="https://agentmods.dev/skills/7tocr/paper2patent/paper2patent"><img src="https://agentmods.dev/badge/skills/7tocr/paper2patent/paper2patent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 23 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00163 | $0.02320 |
| Opus 5.5 | $0.00065 | $0.00928 |
| Sonnet 5.5 | $0.00033 | $0.00464 |
| Haiku 4.5 | $0.00016 | $0.00232 |
Grade A, and why
paper2patent 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 22d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- paper2patent — 100% identical, 0 lines differ
- paper2patent — 86% identical, 110 lines differ
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper2Patent
Convert a paper into a Chinese invention patent application draft that a patent attorney (专利代理师) can review and file with minimal rework. The output is a draft, not legal advice; say so once in the delivery message.
What good looks like
A strong draft does four things the paper itself does not:
- Claims that define a protectable scope. Claim 1 contains exactly the features needed to solve the technical problem (the distinguishing features over the closest prior art) and nothing paper-specific that a competitor could trivially design around. Specific values, model names and optional modules move to dependent claims and embodiments.
- A specification that enables and supports. A skilled person can reproduce the invention from the 具体实施方式 alone, and every claim term is explained there. For AI inventions this means the model's modules/layers/connections, training steps and parameters, and how inputs and outputs map to the application scene (专利审查指南, 2026-01-01 revision).
- Technical character. The solution is framed as technical means solving a technical problem with a technical effect, so it is not rejected as 智力活动的规则和方法 (专利法第25条).
- Complete fidelity. Every technical feature is traceable to the paper. Patent-style generalisation is allowed where the paper supports it; invention is not. Missing information becomes an explicit
【待补充：…】placeholder, never a guess — added matter cannot be supported later and misrepresents the inventors' work.
Workflow
1. Intake
- Pick the mode:
direct(default: draft everything, mark gaps),human-in-loop(confirm disclosure status, invention points and claim plan with the user before drafting),text-only(no files),claims-only, orreview(check an existing draft against the paper). - Read the whole paper: every section, equation, figure, caption, table and appendix. For a PDF, render the pages that contain the method figures and look at them; for text-only input, work from the figure descriptions and captions. The drawings must follow the paper's actual structure. See
references/input-requirements.mdfor PDF handling and the minimum input. - Establish the disclosure status (arXiv? accepted/published? public code? talk?) and dates. This decides whether the patent can still be novel. Read
references/patentability-and-disclosure.md— every time, because the answer changes what you tell the user.
What ships with it
16 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.
- agents/openai.yaml 345 B
- assets/example_patent_content.json 23 KB
- references/claims-and-specification-rules.md 2.7 KB
- references/claims-drafting.md 14 KB
- references/document-generation.md 7.1 KB
- references/drawing-generation.md 8.2 KB
- references/input-requirements.md 3.2 KB
- references/patent-drafting-standard.md 14 KB
- references/patentability-and-disclosure.md 8.7 KB
- references/quality-checklist.md 4.6 KB
- references/text-conversion-workflow.md 4.0 KB
- scripts/check_patent_draft.py 31 KB runs code
- scripts/export_patent_pdf.py 9.8 KB runs code
- scripts/generate_patent_docx.py 34 KB runs code
- scripts/generate_patent_drawings.py 42 KB runs code
- scripts/patent_common.py 13 KB runs code
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.
- 22d ago Changed · +41 lines · +99 tokens per session 1634be409a60
- 1mo ago First seen · 45 lines · 64 tokens per session scan A 761e1245723e
paper2patent is a skill published in the GitHub repository 7toCR/paper2patent (690 stars, last pushed 17d ago), licensed MIT. It adds 163 tokens to every session and 2,320 once invoked, about $0.0007 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 2026-08-30.
Other skills, from other repositories
patent-reader
A plain-language reader for Chinese patents that turns a publication number or PDF into notes, diagrams, and an Obsidian entry. Obsidian is a note-taking app that stores linked Markdown files.
software-copyright-materials
A workflow for creating Chinese application materials for software copyright registration from a real software project.
meta-pdf-reformat-pipeline
Modernize a legacy PDF: structural extraction → natural-language rewrite of problem pages → audit summary → re-merge into the final PDF.
ectd-xml-compiler
Automatically convert uploaded drug application documents (Word/PDF) into XML skeleton structure compliant with eCTD 4.0/3.2.2 specifications.
audit-export
Export the full CocoAudit trail as a stakeholder-ready compliance document.
diagramar-peca
Transforma qualquer peça já escrita (.md ou texto) em um PDF bem diagramado, com Legal Design simples — capa, destaques, citações em bloco, fundamentos e linha do tempo. Não altera o conteúdo, só a forma visual. Use quando quiser entregar uma petição, contrato, parecer ou notificação com aparência profissional e…