Fetch Twitter/X post content by URL without JavaScript or authentication.
Works with
Retrieves full post metadata including author, timestamp, text content, images, and thread replies via Jina.ai API
Supports both individual tweet fetching and batch operations across x.com and twitter.com URLs
Includes bundled Python and Bash scripts for single and multiple tweet retrieval
Requires a free Jina API key set as an environment variable to function
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontwitter-readerExecute the skills CLI command in your project's root directory to begin installation:
Fetches twitter-reader from daymade/claude-code-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate twitter-reader. Access via /twitter-reader in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Fetch Twitter/X post and article content with full media support.
For X Articles with images, use the new fetch_article.py script:
uv run --with pyyaml python scripts/fetch_article.py <article_url> [output_dir]
Example:
uv run --with pyyaml python scripts/fetch_article.py \
https://x.com/HiTw93/status/2040047268221608281 \
./Clippings
This will:
twitter-cli (likes, retweets, bookmarks)jina.ai APIattachments/YYYY-MM-DD-AUTHOR-TITLE/Fetching: https://x.com/HiTw93/status/2040047268221608281
--------------------------------------------------
Getting metadata...
Title: 你不知道的大模型训练：原理、路径与新实践
Author: Tw93
Likes: 1648
Getting content and images...
Images: 15
Downloading 15 images...
✓ 01-image.jpg
✓ 02-image.jpg
...
✓ Saved: ./Clippings/2026-04-03-文章标题.md
✓ Images: ./Clippings/attachments/2026-04-03-HiTw93-.../ (15 downloaded)
For simple text-only fetching without authentication:
# Single tweet
curl "https://r.jina.ai/https://x.com/USER/status/TWEET_ID" \
-H "Authorization: Bearer ${JINA_API_KEY}"
# Batch fetching
scripts/fetch_tweets.sh url1 url2 url3
uv (Python package manager)export JINA_API_KEY="your_api_key_here"
# Get from https://jina.ai/
output_dir/
├── YYYY-MM-DD-article-title.md # Main Markdown file
└── attachments/
└── YYYY-MM-DD-author-title/
├── 01-image.jpg
├── 02-image.jpg
└── ...
https://x.com/USER/status/ID (posts)https://x.com/USER/article/ID (long-form articles)https://twitter.com/USER/status/ID (legacy)Full-featured article fetcher with image download:
uv run --with pyyaml python scripts/fetch_article.py <url> [output_dir]
Simple text-only fetcher using Jina API:
python scripts/fetch_tweet.py <tweet_url> [output_file]
Batch fetch multiple tweets (Jina API):
scripts/fetch_tweets.sh <url1> <url2> ...
Old workflow:
curl "https://r.jina.ai/https://x.com/..."
# Manual image extraction and download
New workflow:
uv run --with pyyaml python scripts/fetch_article.py <url>
# Automatic image download, complete Markdown
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
I recommend twitter-reader for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
twitter-reader fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
twitter-reader has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in twitter-reader — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
twitter-reader has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: twitter-reader is focused, and the summary matches what you get after install.
Useful defaults in twitter-reader — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend twitter-reader for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: twitter-reader is focused, and the summary matches what you get after install.
I recommend twitter-reader for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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