Atlas / Skills / langchain-ai / Social Media

Social MediaSAFE

skills/langchain-ai/social-media

The batteries-included agent harness.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
30,614
01

Overview

The batteries-included agent harness.

Read from source at commit fc9893838214OBSERVED · 2026-10-26
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02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: social-media
description: Drafts engaging social media posts, writes hooks, suggests hashtags, creates thread structures, and generates companion images. Use when the user asks to write a LinkedIn post, tweet, Twitter/X thread, social media caption, social post, or repurpose content for social platforms.
---

# 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"
)
```

3. 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)
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-26 · audit v0.4.1 · source sha fc9893838214full audit observations/trust-audit/skill/langchain-ai__social-media.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-26fc9893838214SAFEB89first audit
05

Questions

What does the social-media — langchain-ai/deepagents skill do?

The batteries-included agent harness.

Is social-media — langchain-ai/deepagents safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can social-media — langchain-ai/deepagents access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (fc9893838214), read on 2026-10-26. The repository is watched, and a new audit runs when it changes — this is the first audit.

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