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specification-writing

Write the full patent specification from claims and invention disclosure

Install / Use

npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill specification-writing

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

93/100

Supported Platforms

OpenAI Codex

Our assessment of specification-writing

specification-writing scores 93/100 on our quality scale, 73rd of 464 Content & Media skills we index (top 16%).

Its SKILL.md is 8.0 KB long, well organised into 20 sections with 5 code examples: a thorough specification that gives an agent plenty to work with.

With 16,644 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
12/15
Adoption
18/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 7 days ago, so specification-writing is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

specification-writing compared with similar skills

All 4 of these similar skills score higher than specification-writing; compare them before choosing.

SkillScoreStarsUpdatedFormat
specification-writing (this skill)by wanshuiyin9316.6k7d agoSKILL.md
Agent-Reachby Panniantong10085.5k11d agoCLAUDE.md
headroomby headroomlabs-ai10073.8ktodayCLAUDE.md
rufloby ruvnet10073.3k1d agoCLAUDE.md
CowAgentby zhayujie10047.1ktodayCLAUDE.md

Frequently asked questions

How do I install specification-writing?
Run npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill specification-writing. The install tabs above show the steps for each supported agent.
Which AI agents does specification-writing work with?
It is written for OpenAI Codex, as a SKILL.md file. Other agents that read the same format can often use it too.
Is specification-writing safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is specification-writing still maintained?
The repository was last updated 7 days ago, so specification-writing is actively maintained.

name: specification-writing description: "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." argument-hint: "[claims-path]" allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob, Skill, WebSearch, WebFetch, mcp__codex__codex, mcp__codex__codex-reply

Specification Writing: Section-by-Section Patent Description

Write the patent specification based on: $ARGUMENTS

Adapted from /paper-write for patent specifications. The specification supports the claims -- it is not a paper.

Constants

  • REVIEWER_MODEL = gpt-6-astra — External reviewer for specification quality
  • JURISDICTION = "auto" — Inherit from pipeline or detect from args; CN, US, EP, ALL
  • OUTPUT_FORMAT = "markdown" — Markdown drafts; converted to filing format by /jurisdiction-format
  • OUTPUT_DIR = "patent/" — Base output directory
  • LANGUAGE = "auto" — Auto from jurisdiction: CN->Chinese, US/EP->English

Inputs

  1. patent/CLAIMS.md — the drafted claims (primary source)
  2. patent/INVENTION_DISCLOSURE.md — invention decomposition
  3. patent/PRIOR_ART_REPORT.md — for background section
  4. User-provided figures (if any)

Shared References

Load ../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.

Workflow

Step 1: Initialize Specification Structure

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

Step 2: Write Title (发明名称)

  • Must match the broadest claim scope
  • No trademarks, no "improved" or "new" or "novel"
  • CN format: "一种[领域]的[技术主题]" or "[领域]的[技术主题]装置"
  • US/EP format: "[Technical topic] for [purpose]" or "[Technical topic] and method thereof"
  • Keep concise (CN: typically under 25 characters; US: under 500 characters)

Step 3: Write Technical Field (技术领域)

1-2 paragraphs identifying the technical domain:

  • "The present invention relates to [broad field], and more particularly to [specific area]."
  • CN: "本发明涉及[技术领域],具体涉及[具体领域]。"

Step 4: Write Background (背景技术)

This is NOT a literature review. It directly sets up the problem.

Structure:

  1. Describe the closest prior art approaches (2-3 paragraphs)
  2. Identify specific technical deficiencies of each approach
  3. The deficiencies must be technical, not commercial or social
  4. DO NOT admit the prior art is "superior" or "better"
  5. DO NOT cite specific patent numbers unless they are known prior art (citations go in IDS for US, or Background section for CN)

CN format: "背景技术" section describing existing technology and its shortcomings.

Step 5: Write Summary (发明内容)

Three parts, directly mirroring INVENTION_DISCLOSURE.md:

Technical Problem (要解决的技术问题):

  • State the problem derived from background deficiencies
  • CN: "本发明要解决的技术问题是..."

Technical Solution (技术方案):

  • Describe how the invention solves the problem
  • Must provide support for ALL claim elements
  • Start from the broadest claim and describe the core inventive concept
  • CN: "为解决上述技术问题,本发明采用的技术方案是:..."
  • NO formulas, NO mathematical derivations, NO circuit models — these belong in 具体实施方式, not 发明内容

Advantages (有益效果):

  • Benefits derived from the structural/technical features (qualitative reasoning)
  • CN: "本发明的有益效果是:..."
  • NO specific numerical results (e.g., "detection limit 70μm", "response time 105ms") — these are experimental findings, not invention properties
  • Frame advantages structurally: "由于采用了...结构,因此具有...效果"

Step 6: Write Brief Description of Drawings (附图说明)

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:

  • CN: "图1是...的示意图;图2是...的流程图;"
  • US: "FIG. 1 is a block diagram showing...; FIG. 2 is a flowchart illustrating..."

Step 7: Write Detailed Description (具体实施方式)

Invoke /embodiment-description as a sub-skill:

/embodiment-description "patent/CLAIMS.md"

This section must:

  • Describe at least one complete embodiment with reference numerals
  • Enable a POSITA to make and use the invention
  • Support every claim element with explicit description
  • Include variations and alternatives for broader claim interpretation

Step 8: Write Abstract (摘要)

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:

  1. The technical field
  2. The problem being solved
  3. The technical solution (core features)
  4. Key advantages

Step 9: Claim Support Verification

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.

Step 10: Cross-Model Review

Call REVIEWER_MODEL via mcp__codex__codex with xhigh reasoning:

mcp__codex__codex:
  model: gpt-6-astra
  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?

Step 11: Output

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 |

Key Rules

  • The specification supports the claims, not the other way around. Every claim element must have support.
  • Use consistent terminology -- same word for the same concept throughout.
  • DO NOT include experimental results, accuracy metrics, or empirical evaluations.
  • DO NOT use subjective language ("excellent", "surprising", "superior").
  • Reference numerals must be consistent: same component, same numeral, everywhere.
  • Background section describes specific deficiencies, not general "need for improvement."
  • Multiple embodiments strengthen the specification but are not always required.
  • Large file handling: if a Write operation fails, retry with Bash cat <<'EOF' heredoc.
  • If mcp__codex__codex is not available, skip cross-model review and note it in the output.

Related Skills

View on GitHub
GitHub Stars16.6k
CategoryContent
Updated7d ago
Forks1.4k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions