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lovstudio%3afill-web-formlovstudio%3a 填写网络表单

Agent Skill

lovstudio%3afill-web-form 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

931

周安装

40

GitHub Stars

45

下载量

326
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:lovstudio%3afill-web-form(lovstudio%3a 填写网络表单)
来源仓库:https://github.com/lovstudio/skills
仓库路径:skills/lovstudio%3Afill-web-form
安装命令:
npx skills add https://github.com/lovstudio/skills --skill lovstudio:fill-web-form
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/lovstudio/skills --skill lovstudio:fill-web-form

简介

lovstudio%3afill-web-form 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用该技能。
  • 安装前需确认权限范围和维护状态,注意可能触发联网、命令执行或文件读写操作。
  • 建议结合原始 README 和仓库内容进一步核验具体功能和用法边界。

SKILL.md

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 WebFetch 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 WebFetch call to get the exact option text for each.

Step 2: Deep-search local knowledge base

Launch an Agent (subagent_type: Explore, thoroughness: very thorough) to search the user's knowledge base. The agent prompt MUST include:

  1. The complete list of form fields from Step 1
  2. 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

  1. Search locations (adapt to user's repo structure):

- Profile/about files (**/profile/**, **/about/**, **/bio/**) - CLAUDE.md files for project context - Posts and articles directories - Project directories - Any official.md, awards.md, resume files

  1. Also check user memory (MEMORY.md) for cached info

Run this in parallel with any additional WebFetch calls from Step 1.

Step 3: Map fields to content

For each form field, synthesize the best answer from search results:

Field TypeStrategy
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/selectPick the best-matching option based on profile
File uploadMark 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:

---
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 **✅ 选择:**
  • For file uploads: use > ⚠️ 需上传:<specs>
  • For private fields: use > ⚠️ 需手动填写(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:
---

## 附录:检索文件路径

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:

  1. A summary table of all fields with fill status
  2. Count of auto-filled vs needs-manual fields
  3. Remind user which fields need manual action (uploads, private data)
  4. The inspected files tree (same as in the document appendix, for quick review)

Key Principles

  1. Pre-fill aggressively — search deeply, compose content, don't leave blanks
  2. Meet all constraints — character minimums, bullet point counts, etc.
  3. Match form tone — conference apps need professional language, registrations can be brief
  4. Respect privacy — never guess phone numbers or passwords, mark for manual input
  5. Cite sources — when composing from knowledge base, the content should be accurate to the user's real experience

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.2%
按下载量换算115

Claude

32%
按下载量换算104

Cursor

20.83%
按下载量换算68

Gemini CLI

8.78%
按下载量换算29

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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