Write the full patent specification from claims and invention disclosure. Use when user says \"撰写说明书\", \"write specification\", \"写说明书\", \"patent description\", or wants to draft the complete patent specification.
npx skills add https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --skill specification-writing
Write the patent specification based on: $ARGUMENTS
Adapted from /paper-write for patent specifications. The specification supports the claims -- it is not a paper.
REVIEWER_MODEL = gpt-5.6-sol — External reviewer for specification qualityJURISDICTION = "auto" — Inherit from pipeline or detect from args; CN, US, EP, ALLOUTPUT_FORMAT = "markdown" — Markdown drafts; converted to filing format by /jurisdiction-formatOUTPUT_DIR = "patent/" — Base output directoryLANGUAGE = "auto" — Auto from jurisdiction: CN->Chinese, US/EP->Englishpatent/CLAIMS.md — the drafted claims (primary source)patent/INVENTION_DISCLOSURE.md — invention decompositionpatent/PRIOR_ART_REPORT.md — for background sectionLoad ../shared-references/patent-writing-principles.md for specification writing rules, language guidelines, and reference numeral conventions.
Load ../shared-references/patent-format-cn.md or patent-format-us.md or patent-format-ep.md based on jurisdiction.
Create the output directory and section files:
patent/specification/
├── title.md
├── technical_field.md
├── background.md
├── summary.md
├── drawings_description.md
├── detailed_description.md
└── abstract.md
1-2 paragraphs identifying the technical domain:
This is NOT a literature review. It directly sets up the problem.
Structure:
CN format: "背景技术" section describing existing technology and its shortcomings.
Three parts, directly mirroring INVENTION_DISCLOSURE.md:
Technical Problem (要解决的技术问题):
Technical Solution (技术方案):
Advantages (有益效果):
Invoke /figure-description as a sub-skill if user has provided figures:
/figure-description "patent/figures/"
If no user figures, describe what figures should exist based on the claims.
Format:
Invoke /embodiment-description as a sub-skill:
/embodiment-description "patent/CLAIMS.md"
This section must:
Jurisdiction-specific word limits:
| Jurisdiction | Word Limit | Notes |
|-------------|-----------|-------|
| CN | 300 words (Chinese characters) | Include most representative claim reference |
| US | 150 words (2500 characters) | Enable efficient searching, no legal phrases |
| EP | ~150 words | No statements on merits or value |
The abstract summarizes:
Verify every claim element finds support in the specification:
| Claim | Element | Specification Section | Paragraph(s) | Reference Numeral |
|-------|---------|----------------------|-------------|-------------------|
| 1 | step a | detailed_description | ¶3 | 202 |
| 1 | step b | detailed_description | ¶4 | 204 |
| X | component A | detailed_description | ¶2 | 102 |
If any element lacks support, add the necessary description before proceeding.
Call REVIEWER_MODEL via mcp__codex__codex with xhigh reasoning:
mcp__codex__codex:
model: gpt-5.6-sol
config: {"model_reasoning_effort": "xhigh"}
prompt: |
You are a patent examiner reviewing a specification for completeness.
CLAIMS: [all claims]
SPECIFICATION: [all specification sections]
Check for:
1. Written description support: Does every claim element have explicit or inherent support?
2. Enablement: Can a POSITA practice the invention from this specification?
3. Consistency: Do reference numerals match across figures and specification?
4. Language quality: Any subjective terms, relative terms without definition, or result-to-be-achieved language?
5. Missing embodiments: Are there claim features that need additional embodiments?
6. Background deficiencies: Are they technical and specific enough?
All specification sections are in patent/specification/.
Summary file: patent/specification/SPECIFICATION_INDEX.md with:
## Patent Specification
### Sections
| Section | File | Word Count | Status |
|---------|------|-----------|--------|
| Title | title.md | | Complete |
| Technical Field | technical_field.md | | Complete |
| Background | background.md | | Complete |
| Summary | summary.md | | Complete |
| Drawings Description | drawings_description.md | | Complete |
| Detailed Description | detailed_description.md | | Complete |
| Abstract | abstract.md | | Complete |
### Claim Support Status
| Claim | Elements Supported | Elements Missing |
|-------|-------------------|-----------------|
| 1 | All | None |
| X | All | None |
cat <<'EOF' heredoc.mcp__codex__codex is not available, skip cross-model review and note it in the output.Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementing any feature or bugfix, before writing implementation code
Use when you have a spec or requirements for a multi-step task, before touching code
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Use when writing or improving README files. Not all READMEs are the same — provides templates and guidance matched to your audience and project type.
| Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
Official Opentrons Protocol API for OT-2 and Flex robots. Use when writing protocols specifically for Opentrons hardware with full access to Protocol API v2 features. Best for production Opentrons protocols, official API compatibility. For multi-vendor automation or broader equipment control use pylabrobot.
Take wanshuiyin/auto-claude-code-research-in-sleep-specification-writing from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.