Token导航 LogoToken导航TokenDH.com
研究检索执行命令github未标认证来源可访问clear审计通过

inframagics-design基础魔法设计

Agent Skill

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

总安装

242

周安装

10

GitHub Stars

公开资料未说明

下载量

79
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

3

许可证

MIT

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:inframagics-design(基础魔法设计)
来源仓库:https://github.com/junhua/forth-ai-homepage
仓库路径:skills/inframagics-design
安装命令:
npx skills add https://github.com/junhua/forth-ai-homepage --skill inframagics-design
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/junhua/forth-ai-homepage --skill inframagics-design

简介

用于辅助界面设计、视觉规范和交互体验优化,帮助 Agent 生成 UI 方案并检查一致性。

  • 适用于页面结构整理、组件层级改进及响应式表现验证,需结合品牌与设计系统使用。
  • 涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出和对齐问题。
  • 通过 npx skills add 命令从 GitHub 仓库安装,需结合原始 README 核验具体用法。
  • inframagics-design 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Inframagics Design Guide

Product: Inframagics — Agent-native workspace for the next unicorns

Demo: https://inframagics.com

Trigger: When designing, reviewing, or improving Inframagics features, interfaces, or architecture.

Key Reference: Product/inframagics-roles-capabilities.md — Roles, capabilities, MVP scope, and full design philosophy


Design Philosophy: Claude Code for Non-Engineers

Core Analogy

Inframagics mirrors the Claude Code experience for non-technical users:

Claude CodeInframagics
Terminal/CLI interfaceChat interface (Genspark-style)
User mode: Write code, commitUser mode: Submit requests, execute tasks
Admin mode: Create rules/MCP/skillsAdmin mode: Create policies, SOPs, workflows
System evolves as you use itSystem learns and improves over time

Key difference: Inframagics is for people extremely uncomfortable with terminal/CLI.

Unified Interface, Role-Based AI

Same UI for all roles — Only the AI behavior changes:

RoleAI Focus
AdminPolicies, SOPs, settings, system configuration
UserClarify request → Reason → Retrieve policies → Execute
ManagerTeam oversight, approvals, delegation

Self-Improving System

User friction → Admin creates policy → System improves → Future users benefit

This virtuous cycle is why Inframagics replaces the ops team, not just the tools.


Role Framework (Summary)

RoleScalePriorityDescription
Admin10+P0/MVPSystem owner, policy creator, approver
User10+P0/MVPRequest submitter, information seeker
Manager30+P1Team approver, delegator
Policy Owner100+P2Domain specialist
External300+P3Vendors, auditors

MVP Focus: Admin + User, Finance (Expenses) only


1. The Paradigm Shift

Traditional Enterprise Model

Policy Makers → SOPs → Operational Staff → ERP/CRM → End Users
     ↓              ↓           ↓              ↓
  Executives    Documents    Humans      Software
  define       interpret    execute      records

Problems:

  • SI fees: 6-7 figures for setup
  • Policy changes: Weeks + SI involvement
  • Ops team: 10-50 people interpreting rules
  • Knowledge: Scattered across systems/heads

Inframagics Model

Policy Makers → Policies (in system) → AI Agent → End Users
     ↓                   ↓                 ↓
  Executives         Natural           Executes
  define in         language,          policies,
  natural           instant            handles
  language          changes            requests

Value:

  • Setup: Self-service, 4-5 figures max
  • Policy changes: Instant, no SI needed
  • Ops team: Eliminated or minimal
  • Knowledge: Organized, retrievable, contextual

2. Target Audience: Baby-Corns

Definition: Next unicorns — fast-growing startups that will need enterprise systems but don't want enterprise baggage.

Baby-Corn Characteristics

TraitImplication for Design
Growing fastSystem must scale without reimplementation
Lean teamsNo dedicated ops staff; everyone wears hats
Tech-savvy foundersExpect modern UX, no tolerance for legacy
Cash-consciousWon't pay 6-figure SI fees
Agile cultureNeed instant policy changes, not IT tickets
AI-native thinkingExpect AI to do the work, not assist

NOT Our Target

  • Legacy enterprises: Have sunk costs in SAP/Oracle, change-averse
  • SMBs with no growth: Don't need policies, just basic tools
  • Industries with rigid compliance: Healthcare, banking (initially)

Design Implication

Every feature should pass the "baby-corn test":

"Would a 50-person startup with no ops team be able to use this without training or consultants?"

3. Three Core Capabilities

Capability 1: Policies & SOPs

What it replaces: Policy manuals, training documents, approval workflows configured by SIs

How it works:

Policy Maker says: "Purchases over $5000 need VP approval"
                          ↓
        System interprets + confirms understanding
                          ↓
        Policy active immediately, enforced by agent
                          ↓
        End user makes request → Agent applies policy

Key Design Principles:

  1. Natural language in, structured execution out

- Input: "New vendors need finance approval" - System: Parses, confirms, stores structured rule - Never ask policy maker to fill forms

  1. Confirmation before activation

- Show: "I understood this as: [structured interpretation]" - Allow: Edit, adjust, test before going live - Never: Silently activate possibly wrong interpretation

  1. Instant changes, zero downtime

- Policy maker edits policy → Live immediately - No IT ticket, no deployment, no SI call

  1. Conflict detection

- When new policy conflicts with existing, surface it - "This overlaps with [other policy]. How should I prioritize?"

  1. Execution visibility

- Every policy application logged - Policy maker can see: "This policy triggered 47 times this week"

Interface Pattern:

┌─────────────────────────────────────────────────────────┐
│  Define a policy...                              🎤     │
│  ─────────────────────────────────────────────────────  │
│  "Expenses over $500 require manager approval"          │
└─────────────────────────────────────────────────────────┘
                          ↓
┌─────────────────────────────────────────────────────────┐
│  I'll create this policy:                               │
│                                                         │
│  Type: APPROVAL                                         │
│  Trigger: expense.amount > 500                          │
│  Action: Require approval from reporting_manager        │
│                                                         │
│  [Edit]  [Test with example]  [Activate]               │
└─────────────────────────────────────────────────────────┘

Capability 2: Request Handling

What it replaces: Ops team that receives requests, interprets policies, executes tasks

How it works:

End user says: "I need to expense this $800 dinner with client"
                          ↓
        Agent checks policies: "Expenses > $500 need approval"
                          ↓
        Agent: "I'll submit this for manager approval.
                Adding it to Sarah's queue. You'll be notified."
                          ↓
        Sarah approves → Agent completes expense submission

Key Design Principles:

  1. Intent-based, not form-based

- User states what they want - Agent figures out how to do it - Never: "Please fill out form XYZ"

  1. Policy application is transparent

- "This needs approval because [policy X]" - User understands why, not just blocked

  1. Agent handles mechanics, human handles judgment

- Agent: Data entry, routing, notifications - Human: Approval decisions, exceptions

  1. Proactive, not reactive

- Agent: "Your expense report has 3 items waiting. Should I submit?" - Not: User must remember to check status

  1. Graceful escalation

- If agent can't handle, escalate to human clearly - "I'm not sure how to handle [X]. Let me connect you with [person]."

Interface Pattern:

┌─────────────────────────────────────────────────────────┐
│  What do you need?                               🎤     │
│  ─────────────────────────────────────────────────────  │
│  "Bill Acme Corp $15,000 for the consulting project"    │
└─────────────────────────────────────────────────────────┘
                          ↓
┌─────────────────────────────────────────────────────────┐
│  📋 Creating invoice for Acme Corp                      │
│                                                         │
│  Amount: $15,000                                        │
│  Description: Consulting project                        │
│  Due: Net 30 (per your policy for this client)         │
│                                                         │
│  ⚠️ This exceeds $10,000 - requires Finance approval    │
│     I'll route to CFO after you confirm.               │
│                                                         │
│  [Confirm & Route]  [Edit details]  [Cancel]           │
└─────────────────────────────────────────────────────────┘

Capability 3: Knowledge Organization & Retrieval

What it replaces: Confluence, SharePoint, Notion sprawl; tribal knowledge in people's heads

How it works:

User asks: "What's our policy on remote work?"
                          ↓
        Agent searches knowledge base
                          ↓
        Agent: "Remote work policy (updated March 2024):
                - 3 days/week in office minimum
                - Core hours 10am-3pm
                - Equipment stipend $500/year
                Want me to show the full policy or help with something specific?"

Key Design Principles:

  1. Conversational retrieval, not search results

- Don't show: 47 matching documents - Show: The answer, with source citation

  1. Knowledge capture from policies

- Policies automatically become queryable knowledge - "What's the approval limit for travel?" → Finds from policy

  1. Context-aware answers

- Agent knows who's asking - Different answer for manager vs. new hire

  1. Living documentation

- When policy changes, knowledge updates automatically - No stale documentation problem

  1. Capture tribal knowledge

- "How do we usually handle X?" can be saved as knowledge - Turn one-off answers into reusable knowledge

Interface Pattern:

┌─────────────────────────────────────────────────────────┐
│  Ask anything...                                 🎤     │
│  ─────────────────────────────────────────────────────  │
│  "How do I get reimbursed for conference travel?"       │
└─────────────────────────────────────────────────────────┘
                          ↓
┌─────────────────────────────────────────────────────────┐
│  For conference travel reimbursement:                   │
│                                                         │
│  1. Submit expense within 30 days of travel            │
│  2. Include receipts for anything over $25             │
│  3. Per diem is $75/day for meals (no receipts needed) │
│  4. Pre-approval required for international travel     │
│                                                         │
│  📎 Source: Travel Policy (updated Nov 2024)           │
│                                                         │
│  Should I start an expense report for you?             │
│  [Yes, start expense]  [Show full policy]              │
└─────────────────────────────────────────────────────────┘

4. Value Proposition Checklist

Every feature must deliver on at least one:

✅ Eliminates SI Dependency

  • Can policy maker configure without consultant?
  • Is setup self-service?
  • Can changes be made without IT ticket?

✅ Shrinks Operations Team

  • Does this replace a human task?
  • Is the agent doing work, not just assisting?
  • Would a 50-person company NOT need an ops hire for this?

✅ Instant Policy Changes

  • Can policy be changed in natural language?
  • Is the change live immediately?
  • Is there no deployment/release cycle?

✅ Knowledge Always Available

  • Is information retrievable conversationally?
  • Is there a single source of truth?
  • Does it eliminate "ask Bob, he knows"?

Red flags (features that don't fit):

  • "Requires initial setup workshop" ❌
  • "Configure in admin settings" ❌
  • "Integrate with your existing..." ❌ (v1 should be complete)
  • "Training required for advanced features" ❌

5. Design Principles

Principle 1: AI Does, Human Confirms

Wrong: AI assists human doing work
Right: AI does work, human confirms/approves

Wrong: "Here's a draft invoice for you to review and edit"
Right: "I created the invoice. It's ready to send. [Send] [Edit first]"

Principle 2: Natural Language Everything

Wrong: Forms with fields
Right: Conversation that extracts what's needed

Wrong: "Select department: [dropdown]"
Right: "Who's this for?" → Agent figures out department

Principle 3: Policy Before Rejection

Wrong: User submits → Error: "Exceeds limit"
Right: User types intent → "This needs approval because [policy]" → User decides to proceed

User should never be surprised by a policy.

Principle 4: Zero Training for Basic Tasks

Wrong: "See documentation for how to submit expenses"
Right: "I need to expense lunch" → Agent handles everything

If a new employee can't accomplish basic tasks on day 1 without training, we've failed.

Principle 5: Instant Feedback Loop

Wrong: Policy maker defines → Wait days → See if it works
Right: Policy maker defines → Test immediately → See execution in real-time

Principle 6: Context is King

Wrong: Same interface for everyone
Right: Agent knows who you are, what you usually do, what's relevant

"Create invoice" for an AP clerk vs. CFO should feel different.

6. Interface Patterns

Full specification: See Product/inframagics-roles-capabilities.md

Unified Chat Interface (All Roles)

Same UI structure for everyone — inspired by Genspark:

┌──────┬────────────────────────────────────────────────┐
│  +   │                                                │
│ New  │          Inframagics                           │
├──────┤                                                │
│  🏠  │   ┌────────────────────────────────────────┐   │
│ Home │   │ Ask anything, request anything          │   │
├──────┤   │                        [📎] [🎤] [→]  │   │
│  💰  │   └────────────────────────────────────────┘   │
│ Fin  │                                                │
├──────┤   Quick Actions / Recent items                 │
│  👥  │                                                │
│ HR   │                                                │
├──────┤                                                │
│  📦  │                                                │
│ Proc │                                                │
├──────┤                                                │
│  💻  │                                                │
│ IT   │                                                │
├──────┤                                                │
│  ⚙️  │                                                │
│ Set  │                                                │
└──────┴────────────────────────────────────────────────┘

Left sidebar = Business functions directory (collapsible icons) Main area = Universal chat input + context-aware actions

Role-Based AI Behavior

Admin AI focuses on system configuration:

Admin: "Set expense limit to $500 for meals"
AI: ✓ Creating policy: Meal expenses capped at $500
    ✓ Applies to: All employees
    → Policy created. Notify employees?

User AI focuses on request execution:

User: "I had dinner with a client at Nobu, $450"
AI: ✓ Checking policy: Entertainment Expense Policy
    ✓ Amount $450 exceeds $200 → Manager approval required
    → Upload receipt? [📎 Attach]

Manager AI focuses on team oversight:

Manager: "What's pending?"
AI: ✓ 3 requests awaiting approval:
    1. Sarah - $450 client dinner (over policy)
    2. Mike - $89 supplies (auto-approvable)
    → Approve Mike's? [✓ Approve]

Key UX Requirements

  • Single universal input (text + voice + attachments)
  • Sidebar scopes context (clicking Finance focuses AI on Finance)
  • Transparent reasoning (show policy lookups, routing decisions)
  • Action buttons in responses (not forms)
  • No separate admin/user URLs — role determines AI behavior

Anti-patterns to Avoid

  • Form-based anything
  • Module-based navigation (AP, AR, HR tabs)
  • Separate admin/user interfaces
  • Configuration tables and matrices
  • Visual workflow builders
  • Search results instead of answers

7. Anti-Patterns (Inframagics-Specific)

"Requires Consultant to Configure"

Symptom: Feature needs expert setup before use. Fix: Natural language configuration with smart defaults.

"Ops Team Still Needed"

Symptom: Agent assists but human still does the work. Fix: Agent does the work, human only approves/confirms.

"Knowledge Scattered"

Symptom: Information in docs, chat, email, people's heads. Fix: All knowledge in Inframagics, conversationally retrievable.

"IT Ticket for Changes"

Symptom: Policy changes need admin/IT involvement. Fix: Policy maker speaks change, it's live immediately.

"Training Required"

Symptom: Users need onboarding to use basic features. Fix: Intent-based interface that anyone can use immediately.

"Enterprise UX Creep"

Symptom: Adding features that make sense for SAP but not baby-corns. Fix: Apply baby-corn test: Would 50-person startup use this?

"Configuration Over Convention"

Symptom: Lots of settings, options, customization. Fix: Smart defaults that work for 90% of cases.


8. Competitive Positioning

vs. Traditional ERP (SAP, Oracle, NetSuite)

DimensionTraditional ERPInframagics
Setup6-12 months, 6-7 figuresSelf-service, days
Policy changesIT project, weeksNatural language, instant
User trainingWeeks of formal trainingZero training needed
Ops teamRequired (10-50 people)Eliminated
InterfaceTransaction codes, formsConversational

Inframagics advantage: For baby-corns, we're the only option that doesn't require becoming an "enterprise" to use enterprise software.

vs. Modern SaaS (Monday, Notion, Asana)

DimensionModern SaaSInframagics
Policy enforcementManual/honor systemAutomatic, built-in
Approval workflowsBasic or bolt-onNative, natural language
Knowledge retrievalSearch resultsConversational answers
Work executionHuman does itAgent does it

Inframagics advantage: SaaS tools organize work but don't do work. Inframagics agent actually executes.

vs. AI Assistants (Copilots, ChatGPT)

DimensionAI AssistantsInframagics
Policy awarenessNone (generic)Built-in, enforced
System of recordExternalNative
Action capabilitySuggestsExecutes
Knowledge scopeGeneralCompany-specific

Inframagics advantage: Generic copilots don't know your policies or have permission to act. Inframagics is the system AND the agent.


9. Review Checklist

When reviewing Inframagics designs:

Value Delivery

  • Does this eliminate SI dependency?
  • Does this shrink the ops team need?
  • Can policies be changed instantly?
  • Is knowledge retrievable conversationally?

Baby-Corn Fit

  • Would a 50-person startup use this?
  • Is it usable without training?
  • Is setup self-service?
  • Does it avoid "enterprise bloat"?

AI-Native Design

  • Is AI doing the work (not just assisting)?
  • Is input natural language (not forms)?
  • Are policies shown before rejection?
  • Is context used to personalize?

Interface Quality

  • Is there a single universal input?
  • Are action options clear?
  • Is status always visible?
  • Can users accomplish goals in <30 seconds?

10. Feature Prioritization Framework

When deciding what to build:

Must Have (P0)

  • Directly eliminates ops team need
  • Enables instant policy changes
  • Core to "agent does work" promise

Should Have (P1)

  • Enhances core capabilities
  • Improves baby-corn experience
  • Requested by multiple prospects

Nice to Have (P2)

  • Edge cases
  • Power user features
  • Future enterprise needs

Won't Build (v1)

  • Requires SI to implement
  • Only relevant for large enterprises
  • Adds complexity without clear value
  • "Because SAP has it"

11. Key Metrics

Agent Effectiveness

  • Tasks completed by agent: Target 80%+
  • Tasks requiring human intervention: Target <20%
  • Policy violations caught pre-submission: Target 95%+

User Adoption

  • Time to first task completion: Target <5 min
  • Tasks per user per week: Growing week-over-week
  • Users needing support: Target <10%

Value Delivery

  • Ops team size: Should be smaller than comparable companies
  • Policy change time: Target <1 hour
  • Setup time: Target <1 day for basic use

12. The Inframagics Promise

To baby-corn founders:

"You'll never need a 50-person ops team. You'll never pay 7-figure SI fees. You'll never wait weeks for policy changes. Your AI agent handles operations. You focus on growth."

Every design decision should reinforce this promise.

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

04

需要参考平台分布和安装热度时

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

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

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

Claude Code

28.18%
按下载量换算22

windsurf

22.41%
按下载量换算18

OpenCode

17.94%
按下载量换算14

Codex

11.8%
按下载量换算9

Antigravity

7.56%
按下载量换算6

Gemini CLI

3.68%
按下载量换算3

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/junhua/forth-ai-homepage --skill inframagics-design;npx skills add junhua/forth-ai-homepage --skill "inframagics-design" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。

来源信息

继续浏览同类 Skills