Lov Fill Form

fill-form — Fill Word Form Templates

This skill fills in Word document form templates (.docx) with user-provided data. It detects table-based form fields (label in one cell, value in the adjacent cell) and populates them automatically.

When to Use

• User has a .docx form template with blank fields to fill
• User wants to fill in an application form, registration form, etc.
• Document uses Word tables for form layout (label | value cell pairs)
• User mentions 填表, 申请表, 登记表, or wants to automate form filling

Workflow (MANDATORY)

You MUST follow these steps in order:

Step 1: Scan the template

Discover all fillable fields:

python lov-fill-form/scripts/fill_form.py --template <path> --scan

Step 2: Pre-fill from known context

Before asking the user, try to fill as many fields as possible from:

1. User memory — name, title, organization, etc.
2. Context files — if the user provides reference documents (e.g. STARTER-PROMPT.md, project docs), extract relevant info to fill content-heavy fields
3. Conversation context — anything already mentioned

For content-heavy fields (e.g. "主要内容/简介/摘要"), actively compose the content by synthesizing from context files, user's known expertise, and the topic/title.

Step 3: Ask only what you don't know

Use AskUserQuestion to collect ONLY the fields you cannot fill from context.

• Group fields into a single question
• If ALL fields are unknown, list them all
• If the user says some fields can be left blank (e.g. "其他朋友会帮我填"), respect that and leave those empty
• Do NOT force the user to provide every field

Step 4: Fill and save

Write a JSON data file (avoids shell escaping issues with long text), then run:

python lov-fill-form/scripts/fill_form.py \
  --template <path> \
  --data-file /tmp/form_data.json

Output path rules:

• Default: <template_dir>/<name>_filled.docx (same directory as the template)
• If the template is in a temp directory or system path, save to user's document directory or ask the user where to save
• Use --output to override explicitly

CLI Reference

How Field Detection Works

1. Table-based (primary): Scans all tables for rows with label→value cell pairs. A label cell contains short text (CJK or Latin); the adjacent cell is the value field.
2. Merged rows: Detects full-width merged cells with "Label：" pattern as large text areas.
3. Paragraph fallback: If no tables found, detects "Label：value" patterns in paragraphs.

Limitations

• .doc files are auto-converted to .docx via macOS textutil, which loses table structure. For best results, use .docx templates directly. If you only have .doc, convert with LibreOffice first: libreoffice --headless --convert-to docx file.doc
• Fields are matched by normalized label text (whitespace removed). If a label contains unusual formatting, the match may fail — use --scan to verify detection.

Dependencies

python3 -m pip install python-docx

Runtime context (shared)

运行前读取本 Skill 包的 skill.yaml，由宿主提供 skill-runtime/v1 上下文。字段解析顺序为：当前请求、项目上下文、个人 Preferences、品牌 Profile、通用默认值。

• 只使用 Manifest 声明的字段；Profile 保存公开品牌事实，Preferences 保存个人工作偏好。
• required: true 字段缺失时，按 Manifest 的问题配置向用户提出一个聚焦问题；用户明确同意后再保存回答。
• 报错提供可复制的 context_id、字段路径与来源，诊断内容避开秘密、完整私人路径和原始配置。

通用反馈闭环

用户在 Skill 驱动任务中提出修改意见时，继续当前产物前必须执行：

1. 先判断意见是 task-specific（仅本次）还是 reusable（可跨任务复用）。
2. task-specific 只修改当前任务，不改 Skill。
3. reusable 先确定作用域：领域规则先更新对应 canonical Skill；适用于所有 Skill 的规则先更新共享规范。
4. 完成规则更新、版本、lint 与分发核验后，再把修改应用到当前任务。
5. reusable 修改会使此前的“确认”“继续”“发吧”失效；完成当前产物修改和回读后必须停下，等待用户下一步指示，不自动进入发布、提交或其他外部写入。