reddit-fetch▌
ykdojo/claude-code-tips · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Use Gemini CLI via tmux. It can browse, summarize, and answer complex questions about Reddit content.
Reddit Fetch
Method 1: Gemini CLI (Try First)
Use Gemini CLI via tmux. It can browse, summarize, and answer complex questions about Reddit content.
Pick a unique session name (e.g., gemini_abc123) and use it consistently throughout.
Setup
tmux new-session -d -s <session_name> -x 200 -y 50
tmux send-keys -t <session_name> 'gemini -m gemini-3-pro-preview' Enter
sleep 3 # wait for Gemini CLI to load
Send query and capture output
tmux send-keys -t <session_name> 'Your Reddit query here' Enter
sleep 30 # wait for response (adjust as needed, up to 90s for complex searches)
tmux capture-pane -t <session_name> -p -S -500 # capture output
If the captured output shows an API error (e.g., quota exceeded, model unavailable), kill the session and retry without the -m flag (just gemini with no model argument). This falls back to the default model.
How to tell if Enter was sent
Look for YOUR QUERY TEXT specifically. Is it inside or outside the bordered box?
Enter NOT sent - your query is INSIDE the box:
╭─────────────────────────────────────╮
│ > Your actual query text here │
╰─────────────────────────────────────╯
Enter WAS sent - your query is OUTSIDE the box, followed by activity:
> Your actual query text here
⠋ Our hamsters are working... (processing)
╭────────────────────────────────────────────╮
│ > Type your message or @path/to/file │
╰────────────────────────────────────────────╯
Note: The empty prompt Type your message or @path/to/file always appears in the box - that's normal. What matters is whether YOUR query text is inside or outside the box.
If your query is inside the box, run tmux send-keys -t <session_name> Enter to submit.
Cleanup when done
tmux kill-session -t <session_name>
If Gemini fails completely
If retrying without -m also fails, fall back to Method 2 below.
Method 2: curl with Reddit JSON API (Fallback)
Reddit's public JSON API works by appending .json to any Reddit URL. Use this when Gemini is unavailable (quota exhausted, API errors, etc.).
Listing hot/new/top posts
curl -s -L -H "User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" \
"https://old.reddit.com/r/SUBREDDIT/hot.json?limit=15"
Replace hot with new, top, or rising as needed. For top, add &t=day (or week, month, year, all).
Fetching a specific post + comments
curl -s -L -H "User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" \
"https://old.reddit.com/r/SUBREDDIT/comments/POST_ID.json?limit=20"
The response is a JSON array: [0] is the post, [1] is the comment tree.
Searching within a subreddit
curl -s -L -H "User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" \
"https://old.reddit.com/r/SUBREDDIT/search.json?q=QUERY&restrict_sr=on&sort=new&limit=15"
Parsing the JSON
Use jq to extract what you need:
# List posts
curl -s -L -o /tmp/reddit_result.txt -w "%{http_code}" \
-H "User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" \
'https://old.reddit.com/r/SUBREDDIT/hot.json?limit=15'
jq -r '.data.children[] | .data | "\(.title)\n \(.score) pts | \(.num_comments) comments | u/\(.author) | id: \(.id)\n"' /tmp/reddit_result.txt
# List comments from a specific post (the [1] element has comments)
jq -r '.[1].data.children[] | select(.kind == "t1") | .data | "u/\(.author) (\(.score) pts):\n \(.body[:300])\n"' /tmp/reddit_thread.txt
Key details:
- Fetch to temp file first, then parse - avoids pipe-related encoding issues
-o /tmp/fileand-w "%{http_code}"saves the response and prints the HTTP status (useful for debugging empty responses)-Lfollows redirects (old.reddit.com sometimes redirects)- Single-quoted URL avoids shell interpretation of
&in query strings .body[:300]truncates long comment bodies (jq 1.7+)
Rate limiting
Reddit's JSON API rate-limits aggressively:
- Don't fire parallel requests. Make them sequentially with
sleep 2orsleep 3between each. - If a request returns empty (0 bytes), wait 3-5 seconds and retry.
- If you get HTTP 429, back off for 10-15 seconds.
- A good pattern: fetch one search result listing, parse it, then fetch individual threads one at a time with delays.
How to use reddit-fetch on Cursor
AI-first code editor with Composer
Prerequisites
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 reddit-fetch
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches reddit-fetch from GitHub repository ykdojo/claude-code-tips and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate reddit-fetch. Access the skill through slash commands (e.g., /reddit-fetch) 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.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
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
Competitive Analysis
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
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ 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.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★66 reviews- ★★★★★Mei Thomas· Dec 24, 2024
Solid pick for teams standardizing on skills: reddit-fetch is focused, and the summary matches what you get after install.
- ★★★★★Li Robinson· Dec 24, 2024
Registry listing for reddit-fetch matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Nia Garcia· Dec 12, 2024
reddit-fetch has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Harper Nasser· Dec 12, 2024
Keeps context tight: reddit-fetch is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Kiara Ghosh· Dec 8, 2024
reddit-fetch fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Carlos Gonzalez· Nov 27, 2024
We added reddit-fetch from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ava Tandon· Nov 15, 2024
reddit-fetch reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Henry Brown· Nov 11, 2024
Solid pick for teams standardizing on skills: reddit-fetch is focused, and the summary matches what you get after install.
- ★★★★★Li Martinez· Nov 3, 2024
I recommend reddit-fetch for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Hassan Smith· Nov 3, 2024
Keeps context tight: reddit-fetch is the kind of skill you can hand to a new teammate without a long onboarding doc.
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