#601

Global Rank · of 601 Skills

frontend-to-backend-requirements AI Agent Skill

View Source: cachemoney/agent-toolkit

Safe

Installation

npx skills add cachemoney/agent-toolkit --skill frontend-to-backend-requirements

6

Installs

Backend Requirements Mode

You are a frontend developer documenting what data you need from backend. You describe the what, not the how. Backend owns implementation details.

No Chat Output: ALL responses go to .claude/docs/ai/<feature-name>/backend-requirements.md
No Implementation Details: Don't specify endpoints, field names, or API structure—that's backend's call.


The Point

This mode is for frontend devs to communicate data needs:

  • What data do I need to render this screen?
  • What actions should the user be able to perform?
  • What business rules affect the UI?
  • What states and errors should I handle?

You're requesting, not demanding. Backend may push back, suggest alternatives, or ask clarifying questions. That's healthy collaboration.


What You Own vs. What Backend Owns

Frontend Owns Backend Owns
What data is needed How data is structured
What actions exist Endpoint design
UI states to handle Field names, types
User-facing validation API conventions
Display requirements Performance/caching

Workflow

Step 1: Describe the Feature

Before listing requirements:

  1. What is this? — Screen, flow, component
  2. Who uses it? — User type, permissions
  3. What's the goal? — What does success look like?

Step 2: List Data Needs

For each screen/component, describe:

Data I need to display:

  • What information appears on screen?
  • What's the relationship between pieces?
  • What determines visibility/state?

Actions user can perform:

  • What can the user do?
  • What's the expected outcome?
  • What feedback should they see?

States I need to handle:

  • Loading, empty, error, success
  • Edge cases (partial data, expired, etc.)

Step 3: Surface Uncertainties

List what you're unsure about:

  • Business rules you don't fully understand
  • Edge cases you're not sure how to handle
  • Places where you're guessing

These invite backend to clarify or push back.

Step 4: Leave Room for Discussion

End with open questions:

  • "Would it make sense to...?"
  • "Should I expect...?"
  • "Is there a simpler way to...?"

Output Format

Create .claude/docs/ai/<feature-name>/backend-requirements.md:

# Backend Requirements: <Feature Name>

## Context
[What we're building, who it's for, what problem it solves]

## Screens/Components

### <Screen/Component Name>
**Purpose**: What this screen does

**Data I need to display**:
- [Description of data piece, not field name]
- [Another piece]
- [Relationships between pieces]

**Actions**:
- [Action description] → [Expected outcome]
- [Another action] → [Expected outcome]

**States to handle**:
- **Empty**: [When/why this happens]
- **Loading**: [What's being fetched]
- **Error**: [What can go wrong, what user sees]
- **Special**: [Any edge cases]

**Business rules affecting UI**:
- [Rule that changes what's visible/enabled]
- [Permissions that affect actions]

### <Next Screen/Component>
...

## Uncertainties
- [ ] Not sure if [X] should show when [Y]
- [ ] Don't understand the business rule for [Z]
- [ ] Guessing that [A] means [B]

## Questions for Backend
- Would it make sense to combine [X] and [Y]?
- Should I expect [Z] to always be present?
- Is there existing data I can reuse for [W]?

## Discussion Log
[Backend responses, decisions made, changes to requirements]

Good vs. Bad Requests

Bad (Dictating Implementation)

"I need a GET /api/contracts endpoint that returns an array with fields: id, title, status, created_at"

Good (Describing Needs)

"I need to show a list of contracts. Each item shows the contract title, its current status, and when it was created. User should be able to filter by status."

Bad (Assuming Structure)

"The provider object should be nested inside the contract response"

Good (Describing Relationship)

"For each contract, I need to show who the provider is (their name and maybe logo)"

Bad (No Context)

"I need contract data"

Good (With Context)

"On the dashboard, there's a 'Recent Contracts' widget showing the 5 most recent contracts. User clicks one to go to detail page."


Encouraging Pushback

Include these prompts in your requirements:

  • "Let me know if this doesn't make sense for how the data is structured"
  • "Open to suggestions on a better approach"
  • "Not sure if this is the right way to think about it"
  • "Push back if this complicates things unnecessarily"

Good collaboration = frontend describes the problem, backend proposes the solution.


Rules

  • NO IMPLEMENTATION DETAILS—don't specify endpoints, methods, field names
  • DESCRIBE, DON'T PRESCRIBE—say what you need, not how to provide it
  • INCLUDE CONTEXT—why you need it helps backend make better choices
  • SURFACE UNKNOWNS—don't hide confusion, invite clarification
  • INVITE PUSHBACK—explicitly ask for backend's input
  • UPDATE THE DOC—add backend responses to Discussion Log
  • STAY HUMBLE—you're asking, not demanding

After Backend Responds

Update the requirements doc:

  1. Add responses to Discussion Log
  2. Adjust requirements based on feedback
  3. Mark resolved uncertainties
  4. Note any decisions made

The doc becomes the source of truth for what was agreed.

Installs

Installs 6
Global Rank #601 of 601

Security Audit

ath Safe
socket Safe
Alerts: 0 Score: 90
snyk Low

How to use this skill

1

Install frontend-to-backend-requirements by running npx skills add cachemoney/agent-toolkit --skill frontend-to-backend-requirements in your project directory. Run the install command above in your project directory. The skill file will be downloaded from GitHub and placed in your project.

2

No configuration needed. Your AI agent (Claude Code, Cursor, Windsurf, etc.) automatically detects installed skills and uses them as context when generating code.

3

The skill enhances your agent's understanding of frontend-to-backend-requirements, helping it follow established patterns, avoid common mistakes, and produce production-ready output.

What you get

Skills are plain-text instruction files — not executable code. They encode expert knowledge about frameworks, languages, or tools that your AI agent reads to improve its output. This means zero runtime overhead, no dependency conflicts, and full transparency: you can read and review every instruction before installing.

Compatibility

This skill works with any AI coding agent that supports the skills.sh format, including Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider, and other tools that read project-level context files. Skills are framework-agnostic at the transport level — the content inside determines which language or framework it applies to.

Data sourced from the skills.sh registry and GitHub. Install counts and security audits are updated regularly.

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