fill-web-form — Fill Web Forms from Local Knowledge Base
Fetch a web form, extract all fields, deep-search the user's local knowledge
base for matching information, and output a ready-to-use markdown document.
When to Use
- User provides a URL to a web form and wants help filling it
- Conference speaker applications, event registrations, profile forms
- Any scenario where form fields can be answered from existing local materials
Workflow (MANDATORY)
Step 1: Fetch and extract form fields
Use
to retrieve the form page and extract ALL fields:
WebFetch(url, prompt="Extract ALL form fields. For each field list: label,
type (text/textarea/select/radio/checkbox/file), required status, options
if applicable, min length constraints. Return structured list.")
If the form has radio/select fields, make a second
call to get
the exact option text for each.
Step 2: Deep-search local knowledge base
Launch an
(subagent_type: Explore, thoroughness: very thorough) to
search the user's knowledge base. The agent prompt MUST include:
- The complete list of form fields from Step 1
- Instructions to search for:
- Personal/professional bio and profile files
- Speaking/conference history
- Project descriptions and achievements
- Company/organization info
- Published articles and their topics
- Awards, credentials, media mentions
- Search locations (adapt to user's repo structure):
- Profile/about files (, , )
- CLAUDE.md files for project context
- Posts and articles directories
- Project directories
- Any , , files
- Also check user memory (MEMORY.md) for cached info
Run this in parallel with any additional
calls from Step 1.
Step 3: Map fields to content
For each form field, synthesize the best answer from search results:
| Field Type | Strategy |
|---|
| Short text (name, company, city) | Direct extraction from profile |
| Bio/introduction (min chars) | Compose from official bio, expand to meet minimum |
| Long-form (case background, solution) | Synthesize from articles, projects, talks |
| Radio/select | Pick the best-matching option based on profile |
| File upload | Mark as "needs manual upload" with specs |
| Private (phone, email) | Mark as "needs manual input", suggest if found |
Step 4: Generate output document
Write a markdown document with ALL form fields filled. Format:
markdown
---
title: "<Form Name> - 填写内容"
status: draft
---
# <Form Name>
> 表单地址：<URL>
---
## 1. <Field Label>
<Filled content or instruction>
---
## 2. <Field Label>
...
Rules:
- Number every field matching the form order
- For radio/select: prefix chosen option with
- For file uploads: use
- For private fields: use （with suggestion if available）
- For textarea fields with min length: ensure content meets or exceeds minimum
- Include a summary table at the end showing field → status (filled/manual)
- MANDATORY: Append an "inspected sources" section at the end of the document
with a tree of all files that were read/searched during knowledge base retrieval:
knowledge-base/
├── profile/
│ └── official.md ← 个人简介
├── posts/standalone/2025/
│ ├── 07-10-Vol-51...md ← 演讲经历
│ └── 06-25-comate...md ← AI工具评测
├── 1-Projects/lovpen/
│ └── ... ← 产品信息
└── CLAUDE.md ← 项目上下文
This tree helps the user verify source coverage and spot missing materials.
Output naming: Follow user's naming convention. Default:
手工川-<form-topic>-<YYYY-MM-DD>-v0.1.md
Step 5: Present summary
After writing the file, show:
- A summary table of all fields with fill status
- Count of auto-filled vs needs-manual fields
- Remind user which fields need manual action (uploads, private data)
- The inspected files tree (same as in the document appendix, for quick review)
Key Principles
- Pre-fill aggressively — search deeply, compose content, don't leave blanks
- Meet all constraints — character minimums, bullet point counts, etc.
- Match form tone — conference apps need professional language, registrations can be brief
- Respect privacy — never guess phone numbers or passwords, mark for manual input
- Cite sources — when composing from knowledge base, the content should be accurate to the user's real experience