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 LingyiChen-AI/OpenSkills --skill feishu-doc-to-dev-specgit clone --depth 1 https://github.com/LingyiChen-AI/OpenSkillsWrote 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/lingyichen-ai/openskills/feishu-doc-to-dev-spec)<a href="https://agentmods.dev/skills/lingyichen-ai/openskills/feishu-doc-to-dev-spec"><img src="https://agentmods.dev/badge/skills/lingyichen-ai/openskills/feishu-doc-to-dev-spec/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/lingyichen-ai/openskills/feishu-doc-to-dev-spec"><img src="https://agentmods.dev/badge/skills/lingyichen-ai/openskills/feishu-doc-to-dev-spec.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 | $0.00052 | $0.01699 |
| Opus 5 | $0.00026 | $0.00849 |
| Sonnet 5 | $0.00010 | $0.00340 |
| Haiku 4.5 | $0.00005 | $0.00170 |
Grade A, and why
feishu-doc-to-dev-spec 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.
How it starts
The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
飞书云文档转研发需求文档
任务目标
本 Skill 用于：
- 读取飞书云文档内容（支持多个文档链接）
- 完整解析文档中的所有内容：文本、表格、图片、代码块等
- 根据用户选择的开发语言和存储结构
- 将产品需求文档（PRD）转换为结构化的研发开发需求文档
前置准备
飞书应用配置
使用前需要创建飞书应用并获取凭证：
- 访问 飞书开放平台
- 创建企业自建应用
- 获取 App ID 和 App Secret
- 配置应用权限：
docx:document:readonly- 读取文档内容drive:drive:readonly- 读取云空间文件wiki:wiki:readonly- 读取知识库（如需要）
环境变量
export FEISHU_APP_ID=your-app-id
export FEISHU_APP_SECRET=your-app-secret
操作步骤
标准流程
-
收集文档链接
- 用户提供一个或多个飞书文档链接
- 支持的链接格式：
https://xxx.feishu.cn/docx/xxxxx- 新版文档https://xxx.feishu.cn/docs/xxxxx- 旧版文档https://xxx.feishu.cn/wiki/xxxxx- 知识库文档
-
确认技术选型
- 询问用户选择的开发语言（如：Python、Java、Go、Node.js、Rust 等）
- 询问存储结构（如：PostgreSQL、MySQL、MongoDB、Redis 等）
- 询问其他技术栈偏好（框架、部署方式等）
-
读取文档内容
- 调用
[INVOKE:fetch_feishu_doc]脚本 - 传入文档链接列表
- 脚本会返回完整的文档内容，包括：
- 文本段落
- 表格数据（转换为 Markdown 表格）
- 图片（下载到本地并返回路径）
- 代码块
- 有序/无序列表
- 调用
-
分析需求内容
- 识别功能需求、非功能需求
- 提取业务规则和约束
- 整理用户故事和验收标准
-
生成研发需求文档
- 根据用户选择的技术栈
- 生成包含以下内容的研发文档：
- 技术架构设计
- 数据模型设计（表结构）
- API 接口设计
- 核心功能实现方案
- 技术风险评估
-
输出结果
- 生成 Markdown 格式的研发需求文档
- 保存到
./output/目录
资源索引
脚本
- 飞书文档读取：
scripts/fetch_feishu_doc.py- 用途：读取飞书云文档的完整内容
- 输入参数（JSON 格式）：
{ "doc_urls": ["https://xxx.feishu.cn/docx/xxxxx"], "app_id": "飞书应用ID（可选，默认从环境变量读取）", "app_secret": "飞书应用密钥（可选，默认从环境变量读取）" } - 输出：文档内容的 JSON 结构
参考文档
-
研发文档模板：
references/dev-spec-template.md- 何时读取：生成研发需求文档时
- 包含标准的研发文档结构和示例
-
技术选型指南：
references/tech-stack-guide.md- 何时读取：帮助用户选择技术栈时
- 包含常见技术栈的特点和适用场景
注意事项
文档权限
- 确保飞书应用有权限访问目标文档
- 如果文档是私有的，需要将应用添加为文档协作者
图片处理
- 文档中的图片会被下载到
./output/images/目录 - 图片链接会被替换为本地相对路径
多文档合并
- 当用户提供多个文档链接时，会按顺序读取并合并内容
- 每个文档的内容会用分隔线区分
输出格式
- 研发需求文档采用 Markdown 格式
- 表格使用 Markdown 表格语法
- 代码块使用对应语言的语法高亮标记
What ships with it
4 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.
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 · 222 lines · 52 tokens per session scan A d56623a2797f
feishu-doc-to-dev-spec is a skill published in the GitHub repository LingyiChen-AI/OpenSkills (68 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 52 tokens to every session and 1,699 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.
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