> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/RightNow-AI/openfang/llms.txt
> Use this file to discover all available pages before exploring further.

# Twitter Hand

> Autonomous Twitter/X manager for content creation, scheduling, and engagement

## Overview

Twitter Hand is an AI-powered social media manager that creates content, manages your posting schedule, handles engagement, and tracks performance — all while maintaining your unique voice.

**Category:** Communication\
**Icon:** 𝕏 (X logo)

## What It Does

<Steps>
  <Step title="Content Research">
    Analyze trending topics in your niche and identify content gaps
  </Step>

  <Step title="Generate Content">
    Create tweets, threads, and replies matching your brand voice
  </Step>

  <Step title="Build Queue">
    Maintain a queue of ready-to-post content (approval mode by default)
  </Step>

  <Step title="Manage Posting">
    Post on schedule or write to queue for your review
  </Step>

  <Step title="Engage">
    Reply to mentions and like relevant content (when enabled)
  </Step>

  <Step title="Track Performance">
    Monitor engagement rates and optimize content strategy
  </Step>
</Steps>

## Requirements

<Warning>
  Twitter Hand requires a Twitter/X Developer account and API access.
</Warning>

### Twitter API Setup

<Steps>
  <Step title="Create Developer Account">
    Go to [developer.twitter.com](https://developer.twitter.com) and sign up
  </Step>

  <Step title="Create Project & App">
    Create a new Project and App in the Developer Portal (free tier works)
  </Step>

  <Step title="Generate Bearer Token">
    Navigate to your App's "Keys and tokens" page and generate a Bearer Token
  </Step>

  <Step title="Set Environment Variable">
    ```bash theme={null}
    export TWITTER_BEARER_TOKEN=your_token_here
    ```
  </Step>

  <Step title="Restart OpenFang">
    Reload config for the token to take effect
  </Step>
</Steps>

**Estimated setup time:** 5-10 minutes

## Configuration

### Content Settings

| Setting            | Options                                                                          | Description                                                                        |
| ------------------ | -------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- |
| **Content Style**  | `professional`, `casual`, `witty`, `educational`, `provocative`, `inspirational` | Voice and tone                                                                     |
| **Content Topics** | Comma-separated                                                                  | Topics to tweet about (e.g., "AI, startups, productivity")                         |
| **Brand Voice**    | Free text                                                                        | Describe your unique voice (e.g., "sarcastic founder who simplifies complex tech") |
| **Thread Mode**    | Toggle                                                                           | Include multi-tweet threads in content mix                                         |

### Posting Schedule

| Setting                | Options                                   | Description                        |
| ---------------------- | ----------------------------------------- | ---------------------------------- |
| **Post Frequency**     | `1_daily`, `3_daily`, `5_daily`, `hourly` | How often to post                  |
| **Content Queue Size** | 5, 10, 20, 50                             | Number of tweets to keep ready     |
| **Approval Mode**      | Toggle (default: ON)                      | Review before posting vs auto-post |

<Note>
  **Approval mode is ON by default** for safety. Tweets are written to a queue file for your review instead of posting automatically.
</Note>

### Engagement Settings

| Setting              | Options                                     | Description                     |
| -------------------- | ------------------------------------------- | ------------------------------- |
| **Auto Reply**       | Toggle                                      | Automatically reply to mentions |
| **Auto Like**        | Toggle                                      | Like tweets from your network   |
| **Engagement Hours** | `business_hours`, `waking_hours`, `all_day` | When to check for engagement    |

## Activation

### Basic Setup

```bash theme={null}
openfang hand activate twitter
```

Configure your voice and topics:

```bash theme={null}
openfang hand config twitter \
  --set content_style="witty" \
  --set content_topics="AI agents, automation, productivity" \
  --set brand_voice="Technical founder who makes AI accessible with humor" \
  --set post_frequency="3_daily" \
  --set approval_mode="true"
```

### Example Workflow

```
Style: Witty
Topics: AI agents, automation, productivity
Frequency: 3 tweets per day (8 AM, 12 PM, 5 PM)
Mode: Approval (queue for review)

> Generate 10 tweets about AI agent trends
```

Twitter Hand will:

1. Research trending AI agent topics
2. Generate 10 tweets in witty style
3. Write to `twitter_queue.json`
4. Create human-readable `twitter_queue_preview.md`
5. Notify you that queue is ready for review
6. Wait for your approval to post

## How It Works

### 1. API Initialization

Verifies Twitter API access:

```bash theme={null}
curl -H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
  "https://api.twitter.com/2/users/me"
```

Extracts your `user_id` and `username` for later API calls.

### 2. Content Research

Before generating content:

**Trend analysis:**

```javascript theme={null}
web_search("AI agents trending today")
web_search("productivity latest news")
web_search("automation viral tweets") // for format inspiration only
```

**Performance analysis:**

```bash theme={null}
curl -H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
  "https://api.twitter.com/2/tweets/search/recent?query=AI%20agents&max_results=10&tweet.fields=public_metrics"
```

Identifies:

* What's trending in your topics
* Content gaps (what's NOT being said)
* High-performing tweet formats

### 3. Content Generation

**7 content types in rotation:**

| Type               | Description                      | Example                                                                  |
| ------------------ | -------------------------------- | ------------------------------------------------------------------------ |
| **Hot take**       | Strong opinion on trending topic | "Unpopular opinion: Most 'AI agents' are just chatbots with extra steps" |
| **Thread**         | Deep dive (3-10 tweets)          | "Why agent frameworks are about to eat traditional SaaS 🧵"              |
| **Tip/How-to**     | Actionable advice                | "Build your first AI agent in 5 lines of Python:..."                     |
| **Question**       | Engagement driver                | "What's the hardest part of building AI agents? 🤔"                      |
| **Curated share**  | Link + insight                   | "This article on ReAct agents is 🔥 \[link] Key insight:..."             |
| **Story/Anecdote** | Personal narrative               | "I spent 6 months building agents. Here's what I learned..."             |
| **Data/Stat**      | Interesting data + commentary    | "AI agent API calls grew 400% in Q1. This changes everything because..." |

**Style adaptation:**

```javascript theme={null}
// Professional style
"AI agents represent a fundamental shift in how we interact with software systems."

// Casual style
"ngl ai agents are kinda wild when you see them in action 🤖"

// Witty style
"AI agents are like interns who never sleep, complain, or ask for equity. Perfect."

// Educational style
"Let's break down how AI agents work:
1. LLM generates plan
2. Tools execute actions
3. Results feed back
4. Repeat until done"

// Provocative style
"Hot take: If your 'AI agent' can't handle failures, it's not an agent — it's a script."

// Inspirational style
"Imagine a world where every repetitive task runs itself. We're building that future. ✨"
```

**Tweet rules:**

* 280 characters max (hard limit)
* Front-load hook (first line grabs attention)
* Use line breaks for readability
* 0-2 hashtags max (avoid spam)
* Threads: first tweet must stand alone

### 4. Content Queue

If `approval_mode = true` (default):

**Queue file (`twitter_queue.json`):**

````json theme={null}
[
  {
    "id": "q_001",
    "content": "Unpopular opinion: Most 'AI agents' are just chatbots with extra steps.\n\nReal agents:\n• Plan multi-step workflows\n• Use tools autonomously\n• Recover from failures\n
Chatbots with function calling aren't agents. They're assistants.\n\nThe bar is higher.",
    "type": "hot_take",
    "created": "2026-03-06T10:30:00Z",
    "status": "pending"
  },
  {
    "id": "q_002",
    "content": "Build your first AI agent in 5 lines of Python:\n\n```python\nfrom anthropic import Anthropic\nclient = Anthropic()\nresponse = client.messages.create(\n  model='claude-3-5-sonnet',\n  tools=[calculator, web_search],\n  messages=[{'role': 'user', 'content': 'Research AI trends'}]\n)\n```\n\nThat's it. Claude handles the rest.",
    "type": "tip",
    "created": "2026-03-06T10:31:00Z",
    "status": "pending"
  }
]
````

**Preview file (`twitter_queue_preview.md`):**

````markdown theme={null}
# Twitter Queue — 10 tweets ready

## Tweet 1 (Hot take)
Unpopular opinion: Most 'AI agents' are just chatbots with extra steps.

Real agents:
• Plan multi-step workflows
• Use tools autonomously
• Recover from failures

Chatbots with function calling aren't agents. They're assistants.

The bar is higher.

---

## Tweet 2 (Tip)
Build your first AI agent in 5 lines of Python:

```python
from anthropic import Anthropic
...
````

***

\[... 8 more tweets ...]

````

To approve and post:
1. Review `twitter_queue_preview.md`
2. Edit if needed
3. Tell Twitter Hand: "Post the queue" or "Post tweet #1"

### 5. Posting (Manual Approval or Auto)

If approved:

**Post a tweet:**
```bash
curl -X POST "https://api.twitter.com/2/tweets" \
  -H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"text": "tweet content here"}'
````

**Post a thread:**

```bash theme={null}
# Tweet 1
curl -X POST "https://api.twitter.com/2/tweets" \
  -d '{"text": "Thread hook tweet"}' \
  -o response1.json

# Extract tweet_id from response1.json
FIRST_ID=$(jq -r '.data.id' response1.json)

# Tweet 2 (reply to tweet 1)
curl -X POST "https://api.twitter.com/2/tweets" \
  -d '{"text": "Thread continuation", "reply": {"in_reply_to_tweet_id": "'$FIRST_ID'"}}' \
  -o response2.json

# Repeat for remaining tweets in thread
```

**Rate limits:** Twitter API allows 300 tweets per 3 hours. Twitter Hand respects this automatically.

Logs each posted tweet to `twitter_posted.json`:

```json theme={null}
{
  "id": "1234567890",
  "text": "...",
  "posted_at": "2026-03-06T12:00:00Z",
  "type": "hot_take",
  "metrics": null // updated later
}
```

### 6. Engagement

If `auto_reply` or `auto_like` enabled:

**Check mentions:**

```bash theme={null}
curl -H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
  "https://api.twitter.com/2/users/$USER_ID/mentions?max_results=10&tweet.fields=created_at"
```

**Generate reply** (if auto\_reply enabled):

```javascript theme={null}
// Mention: "@you What's the best agent framework?"
// Generated reply (matching your style):
"Great question! For production, I'd go with LangGraph (flexibility) or Claude's native tool use (simplicity). Depends if you need complex workflows or straightforward tasks."
```

In approval mode, replies go to queue. Otherwise, posted directly.

**Auto-like** (if enabled):

```bash theme={null}
curl -X POST "https://api.twitter.com/2/users/$USER_ID/likes" \
  -H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
  -d '{"tweet_id": "1234567890"}'
```

Like tweets from:

* People who engage with you
* Relevant content in your topics

Max 50 likes per cycle (avoid rate limits).

<Warning>
  **Twitter Hand NEVER:**

  * Argues with trolls
  * Engages with toxic accounts
  * Posts defamatory or harmful content
  * Impersonates others
  * Violates Twitter Terms of Service
</Warning>

### 7. Performance Tracking

Fetch metrics for recent tweets:

```bash theme={null}
curl -H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
  "https://api.twitter.com/2/tweets?ids=ID1,ID2,ID3&tweet.fields=public_metrics"
```

**Response:**

```json theme={null}
{
  "data": [
    {
      "id": "1234567890",
      "text": "...",
      "public_metrics": {
        "retweet_count": 12,
        "reply_count": 8,
        "like_count": 45,
        "quote_count": 3,
        "bookmark_count": 7,
        "impression_count": 2341
      }
    }
  ]
}
```

**Analyze patterns:**

* Which content types perform best?
* Which posting times get most engagement?
* Which topics resonate most?

Stores insights in knowledge graph for future content optimization.

## Output

| File                       | Description                  |
| -------------------------- | ---------------------------- |
| `twitter_queue.json`       | Pending tweets (JSON)        |
| `twitter_queue_preview.md` | Human-readable queue         |
| `twitter_posted.json`      | Posting history with metrics |

## Dashboard Metrics

* **Tweets Posted** — Total tweets published
* **Replies Sent** — Total engagement replies
* **Queue Size** — Current queue size
* **Engagement Rate** — Average engagement rate

## Tips & Best Practices

<Note>
  **For best results:**

  * Start with approval mode ON — review quality before auto-posting
  * Be specific with `brand_voice` — "Technical founder" is better than "professional"
  * Mix content types — all hot takes or all threads gets stale
  * Review performance weekly — refine topics based on what works
  * Keep queue size at 10-20 for flexibility
</Note>

### Common Issues

**"Unauthorized error"**\
Check your Bearer Token: `echo $TWITTER_BEARER_TOKEN`\
Regenerate if needed via Developer Portal.

**"Rate limit exceeded"**\
Twitter limits 300 tweets per 3 hours. Twitter Hand respects this, but manual posting can hit limits.

**"Tweets lack personality"**\
Be more specific in `brand_voice`. Instead of "professional," try "CTO who explains AI like teaching a 5-year-old, with occasional sarcasm."

**"Low engagement"**\
Check performance metrics. Try different content types, posting times, or topics. Engagement takes time to build.

## Advanced Usage

### On-Demand Content

```
Generate 5 tweets about [breaking news topic]
```

### Thread Deep-Dives

```
Write a 10-tweet thread explaining AI agent architectures for developers
```

### Reply to Specific Tweet

```
Reply to this mention with a helpful response: [tweet URL or text]
```

### Performance Analysis

```
Analyze my tweet performance from the last month. What's working?
```

### Export Content Calendar

```bash theme={null}
cat twitter_queue.json | jq -r '.[] | "\(.created): \(.content)"'
```

## Safety & Guidelines

<Warning>
  **Important safety rules:**

  * Approval mode is ON by default for good reason — AI can make mistakes
  * Review tweets before posting to large audiences
  * Never store passwords or API keys in tweets
  * Don't post private information about anyone
  * Block/ignore trolls — never engage negatively
  * Respect Twitter's automation rules and rate limits
</Warning>

## Next Steps

<CardGroup cols={2}>
  <Card title="Clip Hand" icon="film" href="/hands/clip">
    Create video clips to share on Twitter
  </Card>

  <Card title="Researcher Hand" icon="flask" href="/hands/researcher">
    Research trending topics for tweet content
  </Card>
</CardGroup>