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.
npx skills add gabrielmoreira/agent-skills-mirror --skill paper2patentgit clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirrorWrote 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/gabrielmoreira/agent-skills-mirror/paper2patent)<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/paper2patent"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/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/gabrielmoreira/agent-skills-mirror/paper2patent"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/paper2patent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 20d 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.
This is a copy
100% identical to paper2patent — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
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 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.
- 20d 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 gabrielmoreira/agent-skills-mirror (19 stars, last pushed today), 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. It is 100% identical to paper2patent, differing in 0 lines, and is treated as a copy.
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…