cc-skill-project-guidelines-example

This is an example of a project-specific skill. Use this as a template for your own projects.

sickn33/antigravity-awesome-skills|Updated Apr 8, 2026

Works with

Claude CodeCursorClineWindsurfCodexGoose

Installation Guide

Select your AI agent

How to use cc-skill-project-guidelines-example on Cursor

AI-first code editor with Composer

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

›Cursor installed and configured on your machine
›Node.js 16+ with npm — verify with node --version
›Active project directory where you want to add cc-skill-project-guidelines-example

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill cc-skill-project-guidelines-example

Fetches cc-skill-project-guidelines-example from sickn33/antigravity-awesome-skills and configures it for Cursor.

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?

│

│ ── Universal (.agents/skills) ────────────────

│ · Cline · Codex · Goose · Windsurf

│ ●Cursor(selected)

│ · Cursor · Aider · Continue

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/cc-skill-project-guidelines-example

Restart Cursor to activate cc-skill-project-guidelines-example. Access via /cc-skill-project-guidelines-example in your agent's command palette.

⚠

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

›View source on GitHub ›Skills CLI docs ›About Cursor ›What are agent skills?

Documentation

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

Architecture Overview

Tech Stack:

Frontend: Next.js 15 (App Router), TypeScript, React

Backend: FastAPI (Python), Pydantic models

Database: Supabase (PostgreSQL)

AI: Claude API with tool calling and structured output

Deployment: Google Cloud Run

Testing: Playwright (E2E), pytest (backend), React Testing Library

Services:

┌─────────────────────────────────────────────────────────────┐ │ Frontend │ │ Next.js 15 + TypeScript + TailwindCSS │ │ Deployed: Vercel / Cloud Run │ └─────────────────────────────────────────────────────────────┘ │ ▼ ┌─────────────────────────────────────────────────────────────┐ │ Backend │ │ FastAPI + Python 3.11 + Pydantic │ │ Deployed: Cloud Run │ └─────────────────────────────────────────────────────────────┘ │ ┌───────────────┼───────────────┐ ▼ ▼ ▼ ┌──────────┐ ┌──────────┐ ┌──────────┐ │ Supabase │ │ Claude │ │ Redis │ │ Database │ │ API │ │ Cache │ └──────────┘ └──────────┘ └──────────┘

File Structure

project/ ├── frontend/ │ └── src/ │ ├── app/ # Next.js app router pages │ │ ├── api/ # API routes │ │ ├── (auth)/ # Auth-protected routes │ │ └── workspace/ # Main app workspace │ ├── components/ # React components │ │ ├── ui/ # Base UI components │ │ ├── forms/ # Form components │ │ └── layouts/ # Layout components │ ├── hooks/ # Custom React hooks │ ├── lib/ # Utilities │ ├── types/ # TypeScript definitions │ └── config/ # Configuration │ ├── backend/ │ ├── routers/ # FastAPI route handlers │ ├── models.py # Pydantic models │ ├── main.py # FastAPI app entry │ ├── auth_system.py # Authentication │ ├── database.py # Database operations │ ├── services/ # Business logic │ └── tests/ # pytest tests │ ├── deploy/ # Deployment configs ├── docs/ # Documentation └── scripts/ # Utility scripts

Code Patterns

API Response Format (FastAPI)

from pydantic import BaseModel from typing import Generic, TypeVar, Optional T = TypeVar('T') class ApiResponse(BaseModel, Generic[T]): success: bool data: Optional[T] = None error: Optional[str] = None @classmethod def ok(cls, data: T) -> "ApiResponse[T]": return cls(success=True, data=data) @classmethod def fail(cls, error: str) -> "ApiResponse[T]": return cls(success=False, error=error)

Frontend API Calls (TypeScript)

interface ApiResponse<T> { success: boolean data?: T error?: string } async function fetchApi<T>( endpoint: string, options?: RequestInit ): Promise<ApiResponse<T>> { try { const response = await fetch(`/api${endpoint}`, { ...options, headers: { 'Content-Type': 'application/json', ...options?.headers, }, }) if (!response.ok) { return { success: false, error: `HTTP ${response.status}` } } return await response.json() } catch (error) { return { success: false, error: String(error) } } }

Claude AI Integration (Structured Output)

from anthropic import Anthropic from pydantic import BaseModel class AnalysisResult(BaseModel): summary: str key_points: list[str] confidence: float async def analyze_with_claude(content: str) -> AnalysisResult: client = Anthropic() response = client.messages.create( model="claude-sonnet-4-5-20250514", max_tokens=1024, messages=[{"role": "user", "content": content}], tools=[{ "name": "provide_analysis", "description": "Provide structured analysis", "input_schema": AnalysisResult.model_json_schema() }], tool_choice={"type": "tool", "name": "provide_analysis"} ) # Extract tool use result tool_use = next( block for block in response.content if block.type == "tool_use" ) return AnalysisResult(**tool_use.input)

Custom Hooks (React)

import { useState, useCallback } from 'react' interface UseApiState<T> { data: T | null loading: boolean error: string | null } export function useApi<T>( fetchFn: () => Promise<ApiResponse<T>> ) { const [state, setState] = useState<UseApiState<T>>({ data: null, loading: false, error: null, }) Implementation Guide Prerequisites ›Claude Desktop or compatible AI client with skill support ›Clear understanding of task or problem to solve ›Willingness to iterate and refine outputs Time Estimate 15-45 minutes depending on use case complexity Steps 1Install skill using provided installation command 2Test with simple use case relevant to your work 3Evaluate output quality and relevance 4Iterate on prompts to improve results 5Integrate into regular workflow if valuable Common Pitfalls ⚠Expecting perfect results without iteration ⚠Not providing enough context in prompts ⚠Using skill for tasks outside its intended scope ⚠Accepting outputs without review and validation Best Practices ✓ Do +Start with clear, specific prompts +Provide relevant context and constraints +Review and refine all outputs before using +Iterate to improve output quality +Document successful prompt patterns ✗ Don't −Don't use without understanding skill limitations −Don't skip validation of outputs −Don't share sensitive information in prompts −Don't expect skill to replace human judgment 💡 Pro Tips ★Be specific about desired format and style ★Ask for multiple options to choose from ★Request explanations to understand reasoning ★Combine AI efficiency with human expertise When to Use This ✓ Use when Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement. ✗ Avoid when Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion. Learning Path 1Familiarize yourself with skill capabilities and limitations 2Start with low-risk, non-critical tasks 3Progress to more complex and valuable use cases 4Build expertise through regular use and experimentation Related Skills antigravity-design-expert 89 sickn33/antigravity-awesome-skills Frontendsame repokarpathy-guidelines 29 forrestchang/andrej-karpathy-skills Frontendtag: guidelinesfrontend-design 460 anthropics/claude-code Frontendsame categorypremium-frontend-ui 180 github/awesome-copilot Frontendsame categoryui-animation 176 mblode/agent-skills Frontendsame categoryhigh-end-visual-design 141 leonxlnx/taste-skill Frontendsame category Reviews 4.8★★★★★41 reviews N Noor Srinivasan★★★★★Dec 28, 2024 I recommend cc-skill-project-guidelines-example for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area. M Meera Gonzalez★★★★★Dec 24, 2024 We added cc-skill-project-guidelines-example from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront. S Shikha Mishra★★★★★Dec 20, 2024 cc-skill-project-guidelines-example fits our agent workflows well — practical, well scoped, and easy to wire into existing repos. G Ganesh Mohane★★★★★Dec 12, 2024 Keeps context tight: cc-skill-project-guidelines-example is the kind of skill you can hand to a new teammate without a long onboarding doc. M Meera Perez★★★★★Nov 19, 2024 cc-skill-project-guidelines-example reduced setup friction for our internal harness; good balance of opinion and flexibility. S Sakshi Patil★★★★★Nov 3, 2024 cc-skill-project-guidelines-example has been reliable in day-to-day use. Documentation quality is above average for community skills. C Chaitanya Patil★★★★★Oct 22, 2024 Solid pick for teams standardizing on skills: cc-skill-project-guidelines-example is focused, and the summary matches what you get after install. M Meera Li★★★★★Oct 10, 2024 Registry listing for cc-skill-project-guidelines-example matched our evaluation — installs cleanly and behaves as described in the markdown. H Henry Shah★★★★★Oct 10, 2024 cc-skill-project-guidelines-example reduced setup friction for our internal harness; good balance of opinion and flexibility. K Kwame Lopez★★★★★Sep 21, 2024 cc-skill-project-guidelines-example is among the better-maintained entries we tried; worth keeping pinned for repeat workflows. showing 1-10 of 41 1 / 5 Discussion Comments — not star reviews No comments yet — start the thread.

cc-skill-project-guidelines-example

Installation Guide

How to use cc-skill-project-guidelines-example on Cursor

Prerequisites

Run the install command

Select Cursor when prompted

Verify installation

Security Notice

Documentation

List & Monetize Your Skill

Use Cases

Task Automation & Efficiency

Knowledge Enhancement

Quality Improvement

Install Skill

Project Guidelines Skill (Example)

When to Use

Architecture Overview

File Structure

Code Patterns

API Response Format (FastAPI)

Frontend API Calls (TypeScript)

Claude AI Integration (Structured Output)

Custom Hooks (React)

Implementation Guide

Best Practices

When to Use This

Learning Path

Related Skills

antigravity-design-expert

karpathy-guidelines

frontend-design

premium-frontend-ui

ui-animation

high-end-visual-design

Reviews

Discussion