x-api▌
affaan-m/everything-claude-code · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Programmatic interaction with X (Twitter) for posting, reading, searching, and analytics.
X API
Programmatic interaction with X (Twitter) for posting, reading, searching, and analytics.
When to Activate
- User wants to post tweets or threads programmatically
- Reading timeline, mentions, or user data from X
- Searching X for content, trends, or conversations
- Building X integrations or bots
- Analytics and engagement tracking
- User says "post to X", "tweet", "X API", or "Twitter API"
Authentication
OAuth 2.0 Bearer Token (App-Only)
Best for: read-heavy operations, search, public data.
# Environment setup
export X_BEARER_TOKEN="your-bearer-token"
import os
import requests
bearer = os.environ["X_BEARER_TOKEN"]
headers = {"Authorization": f"Bearer {bearer}"}
# Search recent tweets
resp = requests.get(
"https://api.x.com/2/tweets/search/recent",
headers=headers,
params={"query": "claude code", "max_results": 10}
)
tweets = resp.json()
OAuth 1.0a (User Context)
Required for: posting tweets, managing account, DMs, and any write flow.
# Environment setup — source before use
export X_CONSUMER_KEY="your-consumer-key"
export X_CONSUMER_SECRET="your-consumer-secret"
export X_ACCESS_TOKEN="your-access-token"
export X_ACCESS_TOKEN_SECRET="your-access-token-secret"
Legacy aliases such as X_API_KEY, X_API_SECRET, and X_ACCESS_SECRET may exist in older setups. Prefer the X_CONSUMER_* and X_ACCESS_TOKEN_SECRET names when documenting or wiring new flows.
import os
from requests_oauthlib import OAuth1Session
oauth = OAuth1Session(
os.environ["X_CONSUMER_KEY"],
client_secret=os.environ["X_CONSUMER_SECRET"],
resource_owner_key=os.environ["X_ACCESS_TOKEN"],
resource_owner_secret=os.environ["X_ACCESS_TOKEN_SECRET"],
)
Core Operations
Post a Tweet
resp = oauth.post(
"https://api.x.com/2/tweets",
json={"text": "Hello from Claude Code"}
)
resp.raise_for_status()
tweet_id = resp.json()["data"]["id"]
Post a Thread
def post_thread(oauth, tweets: list[str]) -> list[str]:
ids = []
reply_to = None
for text in tweets:
payload = {"text": text}
if reply_to:
payload["reply"] = {"in_reply_to_tweet_id": reply_to}
resp = oauth.post("https://api.x.com/2/tweets", json=payload)
tweet_id = resp.json()["data"]["id"]
ids.append(tweet_id)
reply_to = tweet_id
return ids
Read User Timeline
resp = requests.get(
f"https://api.x.com/2/users/{user_id}/tweets",
headers=headers,
params={
"max_results": 10,
"tweet.fields": "created_at,public_metrics",
}
)
Search Tweets
resp = requests.get(
"https://api.x.com/2/tweets/search/recent",
headers=headers,
params={
"query": "from:affaanmustafa -is:retweet",
"max_results": 10,
"tweet.fields": "public_metrics,created_at",
}
)
Pull Recent Original Posts for Voice Modeling
resp = requests.get(
"https://api.x.com/2/tweets/search/recent",
headers=headers,
params={
"query": "from:affaanmustafa -is:retweet -is:reply",
"max_results": 25,
"tweet.fields": "created_at,public_metrics",
}
)
voice_samples = resp.json()
Get User by Username
resp = requests.get(
"https://api.x.com/2/users/by/username/affaanmustafa",
headers=headers,
params={"user.fields": "public_metrics,description,created_at"}
)
Upload Media and Post
# Media upload uses v1.1 endpoint
# Step 1: Upload media
media_resp = oauth.post(
"https://upload.twitter.com/1.1/media/upload.json",
files={"media": open("image.png", "rb")}
)
media_id = media_resp.json()["media_id_string"]
# Step 2: Post with media
resp = oauth.post(
"https://api.x.com/2/tweets",
json={"text": "Check this out", "media": {"media_ids": [media_id]}}
)
Rate Limits
X API rate limits vary by endpoint, auth method, and account tier, and they change over time. Always:
- Check the current X developer docs before hardcoding assumptions
- Read
x-rate-limit-remainingandx-rate-limit-resetheaders at runtime - Back off automatically instead of relying on static tables in code
import time
remaining = int(resp.headers.get("x-rate-limit-remaining", 0))
if remaining < 5:
reset = int(resp.headers.get("x-rate-limit-reset", 0))
wait = max(0, reset - int(time.time()))
print(f"Rate limit approaching. Resets in {wait}s")
Error Handling
resp = oauth.post("https://api.x.com/2/tweets", json={"text": content})
if resp.status_code == 201:
return resp.json()["data"]["id"]
elif resp.status_code == 429:
how to use x-apiHow to use x-api on Cursor
AI-first code editor with Composer
1Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add x-api
2Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/affaan-m/everything-claude-code --skill x-apiThe skills CLI fetches x-api from GitHub repository affaan-m/everything-claude-code and configures it for Cursor.
3Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?││ ── Universal (.agents/skills) ── always included ────│ • Amp│ • Antigravity│ • Cline│ • Codex│ ●Cursor(selected)│ • Cursor│ • Windsurf4Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/x-apiReload or restart Cursor to activate x-api. Access the skill through slash commands (e.g., /x-api) or your agent's skill management interface.
⚠Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
Additional Resources
List & Monetize Your Skill
Submit your Claude Code skill and start earning
GET_STARTED →Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
✓Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
✓Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
✓Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
general reviewsRatings
4.4★★★★★32 reviews- ★★★★★Kofi Sharma· Dec 28, 2024
I recommend x-api for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Sophia Jackson· Dec 24, 2024
Solid pick for teams standardizing on skills: x-api is focused, and the summary matches what you get after install.
- ★★★★★Dhruvi Jain· Dec 4, 2024
Useful defaults in x-api — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Oshnikdeep· Nov 23, 2024
x-api is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Daniel Rao· Nov 19, 2024
Keeps context tight: x-api is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Diya Verma· Nov 15, 2024
We added x-api from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Diya Dixit· Nov 11, 2024
x-api reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ganesh Mohane· Oct 14, 2024
Keeps context tight: x-api is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Nia Robinson· Oct 10, 2024
x-api is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Dev Perez· Oct 6, 2024
x-api fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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