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.svg" alt="Measured on agentmods" 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 | $0.00064 | $0.01027 |
| Opus 5 | $0.00032 | $0.00513 |
| Sonnet 5 | $0.00013 | $0.00205 |
| Haiku 4.5 | $0.00006 | $0.00103 |
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 9d 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, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper2Patent
Purpose
Use this skill to convert an academic paper into a complete Chinese invention patent application deliverable. The default full-draft output is a Word document (.docx) and, when a converter is available, a PDF copy. Keep the work faithful to the supplied paper: do not invent technical features, embodiments, data, hardware, scenarios, or effects that are not present in the source material.
Workflow
- Determine the output mode. Use
directby default,human-in-loopwhen the user asks to review choices before generation, andtext-onlywhen the user explicitly wants no files. - Collect and assess the paper input. Read
references/input-requirements.mdwhen the user provides partial paper content, a PDF path, source paper figures, figure descriptions, or unclear source material. - Extract the patentable contribution. Build the closed chain of difference point, technical problem, technical solution, and technical effect.
- Draft the structured patent content. Read
references/text-conversion-workflow.mdfor the five-part content model and execution order. Treat the repositoryreference_skills/meterial.mdprompt as the normative source for the five patent sections, claim rules, specification depth, and fidelity constraints. - Apply claim and specification rules. Read
references/claims-and-specification-rules.mdbefore writing or revising claims, background, invention content, or embodiments. - Prepare drawings. Read
references/drawing-generation.md; first derive patent reference drawings from the source paper figures, captions, and method text when available, then align them with the claims and specification. Generate black-and-white SVG reference drawings, converter-compatible PNG fallbacks when possible, and Image2-style refinement prompts. - Generate files for full drafts. Read
references/document-generation.md, then usescripts/generate_patent_drawings.pyto create clean SVG/PNG drawings,scripts/generate_patent_docx.pyto embed them in DOCX, andscripts/export_patent_pdf.pyfor PDF conversion when available. - Run the internal quality pass. Read
references/quality-checklist.mdbefore finalizing.
What ships with it
10 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 271 B
- references/claims-and-specification-rules.md 2.7 KB
- references/document-generation.md 7.5 KB
- references/drawing-generation.md 6.6 KB
- references/input-requirements.md 3.2 KB
- references/quality-checklist.md 3.8 KB
- references/text-conversion-workflow.md 4.0 KB
- scripts/export_patent_pdf.py 14 KB runs code
- scripts/generate_patent_docx.py 31 KB runs code
- scripts/generate_patent_drawings.py 30 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.
- 9d ago First seen · 45 lines · 64 tokens per session scan A 761e1245723e
paper2patent is a skill published in the GitHub repository 7toCR/paper2patent (588 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 1,027 once invoked, about $0.0003 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.
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.
meta-pdf-reformat-pipeline
Modernize a legacy PDF: structural extraction → natural-language rewrite of problem pages → audit summary → re-merge into the final PDF.
software-copyright-materials
A workflow for creating Chinese application materials for software copyright registration from a real software project.
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.
software-certificate-skill
An automated workflow for preparing Chinese software-copyright registration materials from a real software project. It produces application information, an operation manual, and source-code documents with evidence from the project.