social-media

Redacta publicaciones para redes sociales específicas de cada plataforma, con contenido respaldado por investigación e imágenes complementarias generadas. Admite publicaciones de LinkedIn (1.300 caracteres con tono profesional) e hilos de Twitter/X (280 caracteres por tuit con formato 1/🧵). Requiere delegar la investigación a un subagente antes de redactar, y luego leer los hallazgos para garantizar precisión y relevancia. Genera automáticamente imágenes llamativas para redes sociales usando la herramienta generate_social_image con composiciones audaces y de alto contraste optimizadas para tamaños pequeños...

npx skills add https://github.com/langchain-ai/deepagents --skill social-media

Social Media Content Skill

Research First (Required)

Before writing any social media content, you MUST delegate research:

  1. Use the task tool with subagent_type: "researcher"
  2. In the description, specify BOTH the topic AND where to save:
task(
    subagent_type="researcher",
    description="Research [TOPIC]. Save findings to research/[slug].md"
)

Example:

task(
    subagent_type="researcher",
    description="Research renewable energy trends in 2025. Save findings to research/renewable-energy.md"
)
  1. After research completes, read the findings file before writing

Output Structure (Required)

Every social media post MUST have both content AND an image:

LinkedIn posts:

linkedin/
└── <slug>/
    ├── post.md        # The post content
    └── image.png      # REQUIRED: Generated visual

Twitter/X threads:

tweets/
└── <slug>/
    ├── thread.md      # The thread content
    └── image.png      # REQUIRED: Generated visual

Example: A LinkedIn post about "prompt engineering" → linkedin/prompt-engineering/

You MUST complete both steps:

  1. Write the content to the appropriate path
  2. Generate an image using generate_image and save alongside the post

A social media post is NOT complete without its image.

Platform Guidelines

LinkedIn

Format:

  • 1,300 character limit (show more after ~210 chars)
  • First line is crucial - make it hook
  • Use line breaks for readability
  • 3-5 hashtags at the end

Tone:

  • Professional but personal
  • Share insights and learnings
  • Ask questions to drive engagement
  • Use "I" and share experiences

Structure:

[Hook - 1 compelling line]

[Empty line]

[Context - why this matters]

[Empty line]

[Main insight - 2-3 short paragraphs]

[Empty line]

[Call to action or question]

#hashtag1 #hashtag2 #hashtag3

Twitter/X

Format:

  • 280 character limit per tweet
  • Threads for longer content (use 1/🧵 format)
  • No more than 2 hashtags per tweet

Thread Structure:

1/🧵 [Hook - the main insight]

2/ [Supporting point 1]

3/ [Supporting point 2]

4/ [Example or evidence]

5/ [Conclusion + CTA]

Image Generation

Every social media post needs an eye-catching image. Use the generate_social_image tool:

generate_social_image(prompt="A detailed description...", platform="linkedin", slug="your-post-slug")

The tool saves the image to <platform>/<slug>/image.png.

Social Image Best Practices

Social images need to work at small sizes in crowded feeds:

  • Bold, simple compositions - one clear focal point
  • High contrast - stands out when scrolling
  • No text in image - too small to read, platforms add their own
  • Square or 4:5 ratio - works across platforms

Writing Effective Prompts

Include these elements:

  1. Single focal point: One clear subject, not a busy scene
  2. Bold style: Vibrant colors, strong shapes, high contrast
  3. Simple background: Solid color, gradient, or subtle texture
  4. Mood/energy: Match the post tone (inspiring, urgent, thoughtful)

Example Prompts

For an insight/tip post:

Single glowing lightbulb floating against a deep purple gradient background, lightbulb made of interconnected golden geometric lines, rays of soft light emanating outward. Minimal, striking, high contrast. Square composition.

For announcements/news:

Abstract rocket ship made of colorful geometric shapes launching upward with a trail of particles. Bright coral and teal color scheme against clean white background. Energetic, celebratory mood. Bold flat illustration style.

For thought-provoking content:

Two overlapping translucent circles, one blue one orange, creating a glowing intersection in the center. Represents collaboration or intersection of ideas. Dark charcoal background, soft ethereal glow. Minimalist and contemplative.

Content Types

Announcement Posts

  • Lead with the news
  • Explain the impact
  • Include link or next step

Insight Posts

  • Share one specific learning
  • Explain the context briefly
  • Make it actionable

Question Posts

  • Ask a genuine question
  • Provide your take first
  • Keep it focused on one topic

Quality Checklist

Before finishing:

  • Post saved to linkedin/<slug>/post.md or tweets/<slug>/thread.md
  • Image generated alongside the post
  • First line hooks attention
  • Content fits platform limits
  • Tone matches platform norms
  • Has clear CTA or question
  • Hashtags are relevant (not generic)

Más skills de langchain-ai

deepagents-thread-inspector
langchain-ai
Inspecciona y explica conversaciones en el almacén de sesiones SQLite local de Deep Agents Code. Úsalo como respaldo cuando la herramienta de trazado de LangSmith no esté disponible, para…
deepagents-python-quickstart
langchain-ai
Crear un agente local mínimo de Deep Agent en Python siguiendo la guía de inicio rápido oficial, utilizando la búsqueda web nativa del proveedor en lugar de Tavily. Úsalo cuando el usuario quiera…
deepagents-typescript-quickstart
langchain-ai
Crear un agente Deep local mínimo en TypeScript siguiendo la guía de inicio rápido oficial, usando la búsqueda web nativa del proveedor en lugar de Tavily. Usar cuando el usuario…
eval-engineering
langchain-ai
Inspecciona de forma iterativa un repositorio de agentes y los traces opcionales proporcionados por el usuario, entrevista al usuario, y crea, ejecuta y audita los evals de Harbor uno a la vez. Úsalo para…
LangChain RAG Pipeline
langchain-ai
INVOCA ESTA HABILIDAD al construir CUALQUIER sistema de generación aumentada por recuperación (RAG). Cubre cargadores de documentos, RecursiveCharacterTextSplitter, embeddings (OpenAI),…
LangChain Structured Output & HITL
langchain-ai
langchain-structured-output-&-hitl — una habilidad instalable para agentes de IA, publicada por langchain-ai/langchain-skills.
LangSmith Datasets
langchain-ai
INVOCA ESTA HABILIDAD al crear conjuntos de datos de evaluación a partir de trazas O al subir conjuntos de datos a LangSmith O al consultar conjuntos de datos. Cubre tipos de conjuntos de datos (final_response,…
langsmith-evaluator
langchain-ai
INVOCA ESTA HABILIDAD al construir pipelines de evaluación para LangSmith. Cubre tres componentes principales: (1) Creación de Evaluadores - LLM como juez, código personalizado; (2)…