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 ThomasMoreAI/legal-skills-open --skill paper2patentgit clone --depth 1 https://github.com/ThomasMoreAI/legal-skills-openWrote 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/thomasmoreai/legal-skills-open/paper2patent)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/paper2patent"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/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/thomasmoreai/legal-skills-open/paper2patent"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/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 | $0.00064 | $0.01115 |
| Opus 5.5 | $0.00026 | $0.00446 |
| Sonnet 5.5 | $0.00013 | $0.00223 |
| Haiku 4.5 | $0.00006 | $0.00112 |
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 1mo 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
86% identical to paper2patent — 110 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 — 54 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 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.
- 1mo ago First seen · 54 lines · 64 tokens per session scan A 47421e3f8446
paper2patent is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (95 stars, last pushed 15d ago), licensed Apache-2.0. It adds 64 tokens to every session and 1,115 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to paper2patent, differing in 110 lines, and is treated as a copy.
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