| name | twitter-hand-skill |
| version | 1.0.0 |
| description | Expert knowledge for AI Twitter/X management — API v2 reference, content strategy, engagement playbook, safety, and performance tracking |
| runtime | prompt_only |
Twitter/X Management Expert Knowledge
Twitter API v2 Reference
Authentication
Twitter API v2 uses OAuth 2.0 Bearer Token for app-level access and OAuth 1.0a for user-level actions.
Bearer Token (read-only access + tweet creation):
Authorization: Bearer $TWITTER_BEARER_TOKEN
Environment variable: TWITTER_BEARER_TOKEN
Core Endpoints
Get authenticated user info:
curl -s -H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
"https://api.twitter.com/2/users/me"
Response: {"data": {"id": "123", "name": "User", "username": "user"}}
Post a tweet:
curl -s -X POST "https://api.twitter.com/2/tweets" \
-H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
-H "Content-Type: application/json" \
-d '{"text": "Hello world!"}'
Response: {"data": {"id": "tweet_id", "text": "Hello world!"}}
Post a reply:
curl -s -X POST "https://api.twitter.com/2/tweets" \
-H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
-H "Content-Type: application/json" \
-d '{"text": "Great point!", "reply": {"in_reply_to_tweet_id": "PARENT_TWEET_ID"}}'
Post a thread (chain of replies to yourself):
- Post first tweet → get
tweet_id
- Post second tweet with
reply.in_reply_to_tweet_id = first tweet_id
- Repeat for each tweet in thread
Delete a tweet:
curl -s -X DELETE "https://api.twitter.com/2/tweets/TWEET_ID" \
-H "Authorization: Bearer $TWITTER_BEARER_TOKEN"
Like a tweet:
curl -s -X POST "https://api.twitter.com/2/users/USER_ID/likes" \
-H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
-H "Content-Type: application/json" \
-d '{"tweet_id": "TARGET_TWEET_ID"}'
Get mentions:
curl -s -H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
"https://api.twitter.com/2/users/USER_ID/mentions?max_results=10&tweet.fields=public_metrics,created_at,author_id"
Search recent tweets:
curl -s -H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
"https://api.twitter.com/2/tweets/search/recent?query=QUERY&max_results=10&tweet.fields=public_metrics"
Get tweet metrics:
curl -s -H "Authorization: Bearer $TWITTER_BEARER_TOKEN" \
"https://api.twitter.com/2/tweets?ids=ID1,ID2,ID3&tweet.fields=public_metrics"
Response includes: retweet_count, reply_count, like_count, quote_count, bookmark_count, impression_count
Rate Limits
| Endpoint | Limit | Window |
|---|
| POST /tweets | 300 tweets | 3 hours |
| DELETE /tweets | 50 deletes | 15 minutes |
| POST /likes | 50 likes | 15 minutes |
| GET /mentions | 180 requests | 15 minutes |
| GET /search/recent | 180 requests | 15 minutes |
Always check response headers:
x-rate-limit-limit: Total requests allowedx-rate-limit-remaining: Requests remainingx-rate-limit-reset: Unix timestamp when limit resets
Content Strategy Framework
Content Pillars
Define 3-5 core topics ("pillars") that all content revolves around:
Example for a tech founder:
Pillar 1: AI & Machine Learning (40% of content)
Pillar 2: Startup Building (30% of content)
Pillar 3: Engineering Culture (20% of content)
Pillar 4: Personal Growth (10% of content)
Content Mix (7 types)
| Type | Frequency | Purpose | Template |
|---|
| Hot take | 2-3/week | Engagement | "Unpopular opinion: [contrarian view]" |
| Thread | 1-2/week | Authority | "I spent X hours researching Y. Here's what I found:" |
| Tip/How-to | 2-3/week | Value | "How to [solve problem] in [N] steps:" |
| Question | 1-2/week | Engagement | "[Interesting question]? I'll go first:" |
| Curated share | 1-2/week | Curation | "This [article/tool/repo] is a game changer for [audience]:" |
| Story | 1/week | Connection | "3 years ago I [relatable experience]. Here's what happened:" |
| Data/Stat | 1/week | Authority | "[Surprising statistic]. Here's why it matters:" |
Optimal Posting Times (UTC-based, adjust to audience timezone)
| Day | Best Times | Why |
|---|
| Monday | 8-10 AM | Start of work week, checking feeds |
| Tuesday | 10 AM, 1 PM | Peak engagement day |
| Wednesday | 9 AM, 12 PM | Mid-week focus |
| Thursday | 10 AM, 2 PM | Second-highest engagement day |
| Friday | 9-11 AM | Morning only, engagement drops PM |
| Saturday | 10 AM | Casual browsing |
| Sunday | 4-6 PM | Pre-work-week planning |
Tweet Writing Best Practices
The Hook (first line is everything)
Hooks that work:
- Contrarian: "Most people think X. They're wrong."
- Number: "I analyzed 500 [things]. Here's what I found:"
- Question: "Why do 90% of [things] fail?"
- Story: "In 2019, I almost [dramatic thing]."
- How-to: "How to [desirable outcome] without [common pain]:"
- List: "5 [things] I wish I knew before [milestone]:"
- Confession: "I used to believe [common thing]. Then I learned..."
Writing Rules
- One idea per tweet — don't try to cover everything
- Front-load value — the hook must deliver or promise value
- Use line breaks — no wall of text, 1-2 sentences per line
- 280 character limit — every word must earn its place
- Active voice — "We shipped X" not "X was shipped by us"
- Specific > vague — "3x faster" not "much faster"
- End with a call to action — "Agree? RT" or "What would you add?"
Thread Structure
Tweet 1 (HOOK): Compelling opening that makes people click "Show this thread"
- Must stand alone as a great tweet
- End with "A thread:" or "Here's what I found:"
Tweet 2-N (BODY): One key point per tweet
- Number them: "1/" or use emoji bullets
- Each tweet should add value independently
- Include specific examples, data, or stories
Tweet N+1 (CLOSING): Summary + call to action
- Restate the key takeaway
- Ask for engagement: "Which resonated most?"
- Self-reference: "If this was useful, follow @handle for more"
Hashtag Strategy
- 0-2 hashtags per tweet (more looks spammy)
- Use hashtags for discovery, not decoration
- Mix broad (#AI) and specific (#LangChain)
- Never use hashtags in threads (except maybe tweet 1)
- Research trending hashtags in your niche before using them
Engagement Playbook
Replying to Mentions
Rules:
- Respond within 2 hours during engagement_hours
- Add value — don't just say "thanks!" — expand on their point
- Ask a follow-up question — drives conversation
- Be genuine — match their energy and tone
- Never argue — if someone is hostile, ignore or block
Reply templates:
- Agreement: "Great point! I'd also add [related insight]"
- Question: "Interesting question. The short answer is [X], but [nuance]"
- Disagreement: "I see it differently — [respectful counterpoint]. What's your experience?"
- Gratitude: "Appreciate you sharing this! [Specific thing you liked about their tweet]"
When NOT to Engage
- Trolls or obviously bad-faith arguments
- Political flame wars (unless that's your content pillar)
- Personal attacks (block immediately)
- Spam or bot accounts
- Tweets that could create legal liability
Auto-Like Strategy
Like tweets from:
- People who regularly engage with your content (reciprocity)
- Influencers in your niche (visibility)
- Thoughtful content related to your pillars (curation signal)
- Replies to your tweets (encourages more replies)
Do NOT auto-like:
- Controversial or political content
- Content you haven't actually read
- Spam or low-quality threads
- Competitor criticism (looks petty)
Content Calendar Template
WEEK OF [DATE]
Monday:
- 8 AM: [Tip/How-to] about [Pillar 1]
- 12 PM: [Curated share] related to [Pillar 2]
Tuesday:
- 10 AM: [Thread] deep dive on [Pillar 1]
- 2 PM: [Hot take] about [trending topic]
Wednesday:
- 9 AM: [Question] to audience about [Pillar 3]
- 1 PM: [Data/Stat] about [Pillar 2]
Thursday:
- 10 AM: [Story] about [personal experience in Pillar 3]
- 3 PM: [Tip/How-to] about [Pillar 1]
Friday:
- 9 AM: [Hot take] about [week's trending topic]
- 11 AM: [Curated share] — best thing I read this week
Performance Metrics
Key Metrics
| Metric | What It Measures | Good Benchmark |
|---|
| Impressions | How many people saw the tweet | Varies by follower count |
| Engagement rate | (likes+RTs+replies)/impressions | >2% is good, >5% is great |
| Reply rate | replies/impressions | >0.5% is good |
| Retweet rate | RTs/impressions | >1% is good |
| Profile visits | People checking your profile after tweet | Track trend |
| Follower growth | Net new followers per period | Track trend |
Engagement Rate Formula
engagement_rate = (likes + retweets + replies + quotes) / impressions * 100
Example:
50 likes + 10 RTs + 5 replies + 2 quotes = 67 engagements
67 / 2000 impressions = 3.35% engagement rate
Content Performance Analysis
Track which content types and topics perform best:
| Content Type | Avg Impressions | Avg Engagement Rate | Best Performing |
| --- | --- | --- | --- |
| Hot take | 2500 | 4.2% | "Unpopular opinion: ..." |
| Thread | 5000 | 3.1% | "I analyzed 500 ..." |
| Tip | 1800 | 5.5% | "How to ... in 3 steps" |
Use this data to optimize future content mix.
Brand Voice Guide
Voice Dimensions
| Dimension | Range | Description |
|---|
| Formal ↔ Casual | 1-5 | 1=corporate, 5=texting a friend |
| Serious ↔ Humorous | 1-5 | 1=all business, 5=comedy account |
| Reserved ↔ Bold | 1-5 | 1=diplomatic, 5=no-filter |
| General ↔ Technical | 1-5 | 1=anyone can understand, 5=deep expert |
Consistency Rules
- Use the same voice across ALL tweets (hot takes and how-tos)
- Develop 3-5 "signature phrases" you reuse naturally
- If the brand voice says "casual," don't suddenly write a formal thread
- Read tweets aloud — does it sound like the same person?
Safety & Compliance
Content Guidelines
NEVER post:
- Discriminatory content (race, gender, religion, sexuality, disability)
- Defamatory claims about real people or companies
- Private or confidential information
- Threats, harassment, or incitement to violence
- Impersonation of other accounts
- Misleading claims presented as fact
- Content that violates Twitter Terms of Service
Approval Mode Queue Format
[
{
"id": "q_001",
"content": "Tweet text here",
"type": "hot_take",
"pillar": "AI",
"scheduled_for": "2025-01-15T10:00:00Z",
"created": "2025-01-14T20:00:00Z",
"status": "pending",
"notes": "Based on trending discussion about LLM pricing"
}
]
Preview file for human review:
# Tweet Queue Preview
Generated: YYYY-MM-DD
## Pending Tweets (N total)
### 1. [Hot Take] — Scheduled: Mon 10 AM
> Tweet text here
**Notes**: Based on trending discussion about LLM pricing
**Pillar**: AI | **Status**: Pending approval
---
### 2. [Thread] — Scheduled: Tue 10 AM
> Tweet 1/5: Hook text here
> Tweet 2/5: Point one
> ...
**Notes**: Deep dive on new benchmark results
**Pillar**: AI | **Status**: Pending approval
Risk Assessment
Before posting, evaluate each tweet:
- Could this be misinterpreted? → Rephrase for clarity
- Does this punch down? → Don't post
- Would you be comfortable seeing this attributed to the user in a news article? → If no, don't post
- Is this verifiably true? → If not sure, add hedging language or don't post
