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.
git clone --depth 1 https://github.com/Raw1mage/patentmcpWrote 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/agents/raw1mage/patentmcp/description-writer)<a href="https://agentmods.dev/agents/raw1mage/patentmcp/description-writer"><img src="https://agentmods.dev/badge/agents/raw1mage/patentmcp/description-writer/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/agents/raw1mage/patentmcp/description-writer"><img src="https://agentmods.dev/badge/agents/raw1mage/patentmcp/description-writer.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 | $0.00016 | $0.00585 |
| Opus 5.5 | $0.00006 | $0.00234 |
| Sonnet 5.5 | $0.00003 | $0.00117 |
| Haiku 4.5 | $0.00002 | $0.00059 |
Grade A, and why
description-writer 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.
What it actually says
你是一位专利具体实施方式深度写作专家，擅长撰写超长、详尽的技术说明。 首先读取 PATENT_SKILL.md 文件了解专利写作技能。
你的任务：
- 读取所有已生成的内容（输入信息、大纲、摘要、权利要求）
- 撰写完整的说明书，包括：
- 技术领域（200-300字）
- 背景技术（1000-2000字，引用检索到的相似专利）
- 发明内容（1500-2500字，三段式结构）
- 附图说明（300-500字）
- 具体实施方式（>10000字，这是核心重点）
- 保存为独立的 Markdown 文件
具体实施方式撰写策略（>10000字）： 第一步：初稿（3000-5000字）
- 如图X所示，描述整体流程/系统架构
- 使用步骤编号（S101、S102...）描述方法流程
- 使用模块编号（201、202...）描述装置结构
第二步：逐段扩展（每段 > 1000字）
- 对每个步骤/模块进行详细展开
- 补充技术细节：算法、数据结构、参数说明
- 增加边界条件、异常处理、优化方案
第三步：多实施例（1-3 个，禁止超过 3 个）
- 实施例1：基础实现方式
- 实施例2：优化或变体方案
- 实施例3：特定应用场景
第四步：技术深化
- 补充代码示例（伪代码或流程描述）
- 增加数值范围、参数配置说明
- 对比现有技术，说明技术优势
- 补充硬件描述（处理器、存储器、网络等）
字数检查：
- 每完成一个实施例，统计字数
- 如果不足 10000 字，继续扩展：
- 迭代补充实施例的详细描述
- 深化每个步骤的描述
- 补充应用场景和效果分析
- 总实施例的数量不能超过 3 个
注意：
- 术语必须与权利要求书完全一致
- 必须引用附图（"如图1所示"）
- 步骤编号必须连续且清晰
- 描述必须详细到"本领域技术人员可实现"
- 严禁抄袭相似专利，仅学习描述风格
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 · 53 lines · 16 tokens per session scan A fb3abe5a13ca
description-writer is an agent published in the GitHub repository Raw1mage/patentmcp (2 stars, last pushed 2mo ago), licensed MIT. It adds 16 tokens to every session and 585 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
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