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Skills IA Données et IA

Découvrez les skills Données et IA, comparez leurs dépôts et consultez leurs instructions.

Catégories: Données et IA

56,449–56,472 sur 83,104

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Explorer

GitHub

code-review

BoneTheDeveloper

Review code quality, receive feedback with technical rigor, verify completion claims. Use before PRs, after implementing features, when claiming task completion, for subagent reviews.

GitHub

graphite-cli

Calel33

This skill should be used to answer questions and guide workflows related to the Graphite CLI. It assists with creating, managing, submitting, and synchronizing stacked code changes (diffs).

GitHub

repomap

Nicenonecb

Guide for using RepoMap outputs and CLI to locate modules, entry files, and keywords. This skill should be used when users ask to navigate a large repository, find relevant modules/files, or run RepoMap build/u...

GitHub

markdown-frontmatter

ekuris-repos

Add and maintain YAML frontmatter in Markdown files. Use this whenever creating or substantially editing any .md content in this repository.

GitHub

requirements-elicitation

DoubleslashSE

Requirements gathering and elicitation techniques for business analysis. Use when conducting stakeholder interviews, gathering functional/non-functional requirements, or identifying gaps in requirements.

GitHub

frontend-designer

braw-dev

Provides rules and guidelines for design and UI/UX. Must be referred to when working on frontend or user facing elements.

GitHub

onboard-new-role

HcVm

Systematic workflow for introducing a new User Role (e.g., 'Auditor', 'Supervisor') into the ATLAS ecosystem.

GitHub

frontend-philosophy

opzero1

Visual & UI philosophy (The 5 Pillars of Intentional UI). Apply to styling, layout, colors, typography, animations. Avoid "AI slop" aesthetics.

GitHub

srs-documentation

DoubleslashSE

Software Requirements Specification documentation following IEEE 830 standard. Use when generating formal SRS documents or compiling gathered requirements into structured documentation.

GitHub

visual-testing

JaveedIshaq

Run the app locally and take screenshots using Puppeteer to verify UI changes; use when validating demo pages, checking visual regressions, or capturing UI state for analysis

GitHub

tdd-enforcer

Barnhardt-Enterprises-Inc

Use when implementing new features. Enforces TDD workflow - write tests FIRST, then implementation. Ensures AAA pattern, proper coverage, and quality test design.

GitHub

python-testing-patterns

Jeoffreybauvin

Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.

GitHub

web-artifacts-builder

lewbei

Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, rou...

GitHub

vercel-deploy

lewbei

Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as "Deploy my app", "Deploy this to production", "Create a preview deployment", "Deploy and give me the...

GitHub

strapi-integration

AmnadTaowsoam

Integrating with Strapi open-source headless CMS built with Node.js, including setup, content types, customization, API integration, and deployment patterns.

GitHub

contentful-integration

AmnadTaowsoam

Integrating with Contentful headless CMS platform for content management, including setup, content modeling, API integration, and Next.js patterns.

GitHub

headless-cms-integration

AmnadTaowsoam

Separating content management from presentation by providing content via APIs, enabling omnichannel delivery and developer flexibility with platforms like Contentful, Strapi, and Sanity.

GitHub

hashbrown-dev

aaronbassett

Building LLM-powered React applications with the Hashbrown library. Use when the user asks to (1) Build generative UI where LLMs render React components, (2) Add client-side tool calling for LLM-app interaction...

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.

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