lovstudio%3afill-form（lovstudio%3a 填写表格）

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 lovstudio-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 lovstudio-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

pip install python-docx --break-system-packages