Flow2Spec: Skill for Claude Code

.claude/skills/f2s-doc-pdf/SKILL.md

f2s-doc-pdf is a skill for Claude Code from double-coding-lab/Flow2Spec. It costs 41 tokens per session (1,301 once invoked), scanned A, original, MIT.

A document-conversion workflow that turns a technical PDF into a Markdown file and saves it in the project's `.Knowledge/req-docs/` folder. It can also help complete written process descriptions that are missing from diagrams.

In plain words
What is it for?
Use it to convert a local PDF technical proposal into a Markdown requirements document, preserve structures such as tables and code blocks, and collect missing process details from the user.
Why use it?
It avoids manually copying and restructuring a technical proposal before implementation. It also makes diagram-based steps easier to clarify when the PDF's flowcharts cannot be read directly.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: mentions subagents; mentions Codex.

This is double-coding-lab/Flow2Spec's own configuration. It tells Claude Code how to work on Flow2Spec itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Flow2Spec configures →

Reuse

Borrowing it

Nothing to install: this file belongs to double-coding-lab/Flow2Spec. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/double-coding-lab/Flow2Spec/main/.claude/skills/f2s-doc-pdf/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/double-coding-lab/Flow2Spec

Made for: Claude Code.

Wrote 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.

agentmods badge for f2s-doc-pdf

README.md
[![agentmods](https://agentmods.dev/badge/skills/double-coding-lab/flow2spec/f2s-doc-pdf/github.svg)](https://agentmods.dev/skills/double-coding-lab/flow2spec/f2s-doc-pdf)
Your own site
<a href="https://agentmods.dev/skills/double-coding-lab/flow2spec/f2s-doc-pdf"><img src="https://agentmods.dev/badge/skills/double-coding-lab/flow2spec/f2s-doc-pdf/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.

agentmods 80×15 button for f2s-doc-pdf

Your own site · 80×15
<a href="https://agentmods.dev/skills/double-coding-lab/flow2spec/f2s-doc-pdf"><img src="https://agentmods.dev/badge/skills/double-coding-lab/flow2spec/f2s-doc-pdf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,301 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00041 $0.01301
Opus 5.5 $0.00016 $0.00520
Sonnet 5.5 $0.00008 $0.00260
Haiku 4.5 $0.00004 $0.00130

Measured 1mo ago against content hash 075af114f6b4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

f2s-doc-pdf 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.

.claude/skills/f2s-doc-pdf/SKILL.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

执行口径:技术方案文档统一落在 .Knowledge/req-docs/;规则能力仍由配置根 rules/skills 加载。

编排(主 / 子 agent)

  • 两字段(subAgent / switchAgentVerification)语义以统一入口为唯一事实源:Cursor/Claude 读配置根 rules/f2s-flow2spec-unified-entry.*;Codex 读 .codex/topics/f2s-flow2spec-unified-entry.md(与上同源,flow2spec init 镜像)。本文不复述。
  • 默认不拆子:追问-落盘必须在主 agent 内完成(子 agent 无法向用户追问)。
  • 可选拆子:仅当 subAgent=true 且 PDF 规模超阈值(> 50 页 或 > ~5MB 文本)时启用;子 agent 仅负责 PDF→MD 首稿并落盘 .Knowledge/req-docs/<名>.md,不向用户追问、不写「流程说明」章节;主 agent 接手后续追问与流程图补写。
  • 校验默认由落盘侧 agent 自验;本 SKILL 不绑定交叉校验。

将 PDF 技术方案文档转为 Markdown(并补全流程说明)

用户会在本技能后附带一个参数:PDF 技术方案文档的本地路径(如 ~/Downloads/技术方案.pdf,或 .Knowledge/req-docs/某草稿.pdf)。请按以下步骤执行,将 PDF 转为 Markdown 并保存到 .Knowledge/req-docs/,必要时引导用户补全流程说明。

步骤 1:读取 PDF 并转为 Markdown

  1. 若启用拆子(PDF > 50 页 或 > ~5MB),子 agent 仅负责 PDF→MD 首稿并落盘 req-docs/<名>.md,不追问、不写流程说明;主 agent 接手后续步骤。读取用户传入的 PDF 文件,提取其中的文字内容(表格、章节、列表、代码块等尽量保留结构),整理为 Markdown 格式。
  2. 保存到 .Knowledge/req-docs/,推荐路径:.Knowledge/req-docs/<方案名>.md。文件名为原 PDF 文件名去掉 .pdf 后加 .md。
  3. 若目录不存在,先创建再写入。
  4. 保存后告知用户:「已将该 PDF 转为 Markdown 并保存为 xxx.md。」

步骤 2:向用户提问获取流程图(可选但推荐)

PDF 内嵌的流程图无法被直接解析为步骤与分支,若需按图实现代码,需用户配合提供。

  1. 向用户说明:「文档中可能包含流程图,我无法从 PDF 中解析图中的步骤与分支。若您后续会根据技术方案实现代码(见 implement-tech-design 规则),建议补全流程说明:
  • 方式一:将相关流程图以图片形式发到本次对话中,我将解析后以文字形式写入上述 MD;
  • 方式二:直接以文字描述每个接口/流程的步骤(如:1. 是否登录 2. 查某表 3. 判断某字段 → 返回结果),我将原样写入上述 MD。
    若文档无流程图或暂不提供,可回复「跳过」,我将结束本技能。」
  1. 若用户回复「跳过」或明确表示无需流程说明:告知用户「在对话中提供上述 MD 路径并说明按技术方案实现代码,我将按 implement-tech-design 规则执行。」并结束。
  2. 若用户提供流程图(图片或文字):进入步骤 3。

步骤 3:将流程说明写入该 MD

  1. 若用户提供的是图片:解析图片中的步骤、判断分支与返回,整理为文字步骤。
  2. 若用户提供的是文字:直接采用。
  3. 在该 MD 文件末尾(或新增「流程说明」章节)追加流程内容,格式示例:
## 流程说明(由用户提供 / 由流程图解析)

### 示例接口 A
1. 前端发起请求
2. 后端:查询某表最后一条记录
3. 判断:是否有某 ID?是 → 返回 true,否 → 返回 false
4. 返回结果

### 示例接口 B
1. 是否登录 → 否 返回 401
2. 是否过期 → 是 返回 403
…
  1. 保存后告知用户:「流程说明已写入 xxx.md。接下来请在对话中提供该 MD 路径并说明要按技术方案实现代码,我将按 implement-tech-design 规则执行。」

Read the full file on GitHub · 71 lines

Changes

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.

  1. 1mo ago First seen · 71 lines · 41 tokens per session scan A 075af114f6b4

Subscribe to this mod's changes

f2s-doc-pdf is a skill published in the GitHub repository double-coding-lab/Flow2Spec (52 stars, last pushed 6d ago), licensed MIT. It adds 41 tokens to every session and 1,301 once invoked, about $0.0002 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 2026-08-30.

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