jina-cli

geekjourneyx/jina-cli · updated Apr 8, 2026

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$npx skills add https://github.com/geekjourneyx/jina-cli --skill jina-cli
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summary

CLI tool for reading web content and performing AI-powered web searches.

skill.md

jina - Web Content Reader & Search

CLI tool for reading web content and performing AI-powered web searches.

Quick start

Install:

curl -fsSL https://raw.githubusercontent.com/geekjourneyx/jina-cli/main/scripts/install.sh | bash

Basic usage:

# Read a URL
jina read --url "https://example.com"

# Search the web
jina search --query "golang latest news"

Commands

Command Purpose
read Extract and convert content from URLs to LLM-friendly format
search Search the web with AI-powered result processing
config Manage settings (set/get/list/path)

Read command

Extract content from any URL:

# Basic read
jina read --url "https://example.com"

# Read with image captioning
jina read -u "https://x.com/user/status/123" --with-alt

# Batch process from file
jina read --file urls.txt

# Output as Markdown
jina read -u "https://example.com" --output markdown

# Save to file
jina read -u "https://example.com" --output-file result.md

Response formats

The API can return content in different formats via --format:

  • markdown - Default, LLM-friendly Markdown
  • html - Raw HTML
  • text - Plain text
  • screenshot - URL to a screenshot

Advanced options

# Bypass cache
jina read -u "https://example.com" --no-cache

# Use proxy
jina read -u "https://example.com" --proxy "http://proxy.com:8080"

# CSS selector extraction
jina read -u "https://example.com" --target-selector "article.main"

# Wait for element to load
jina read -u "https://example.com" --wait-for-selector "#content"

# Forward cookies
jina read -u "https://example.com" --cookie "session=abc123"

# POST method for SPA with hash routing
jina read -u "https://example.com/#/route" --post

Search command

Search the web with automatic content fetching from top results:

# Basic search
jina search --query "golang latest news"

# Restrict to specific sites
jina search -q "AI developments" --site techcrunch.com --site theverge.com

# Limit results
jina search -q "climate change" --limit 10

# Output format
jina search -q "news" --output markdown

Site filtering

Use multiple --site flags to restrict search to specific domains:

jina search -q "startup funding" --site techcrunch.com --site theverge.com --site wired.com

Configuration

Config file: ~/.jina-reader/config.yaml

Priority: Command args > Environment vars > Config file > Defaults

Environment variables:

  • JINA_API_BASE_URL - Read API URL (default: https://r.jina.ai/)
  • JINA_SEARCH_API_URL - Search API URL (default: https://s.jina.ai/)
  • JINA_TIMEOUT - Request timeout in seconds (default: 30)
  • JINA_WITH_GENERATED_ALT - Enable image captioning (default: false)
  • JINA_OUTPUT_FORMAT - Output format: json/markdown (default: json)
  • JINA_PROXY_URL - Proxy server URL

Config commands:

# Set configuration
jina config set timeout 60
jina config set with-generated-alt true

# View configuration
jina config list
jina config get timeout
jina config path

Output formats

JSON format (default, machine-readable):

{
  "success": true,
  "data": {
    "url": "https://example.com",
    "content": "# Extracted Content\n\n...",
    "title": "Page Title"
  }
}

Markdown format (human-readable):

jina read -u "https://example.com" --output markdown

Common use cases

Reading social media posts

# X (Twitter) posts
jina read -u "https://x.com/elonmusk/status/123456" --with-alt

# The --with-alt flag enables VLM image captioning for embedded images

Reading articles/blogs

# Standard article
jina read -u "https://blog.example.com/article"

# With specific format
jina read -u "https://example.com" --format text --output markdown

Research workflows

# 1. Search for topic
jina search -q "quantum computing 2025" --limit 10

# 2. Read specific results
jina read --file search_results.txt

Batch processing

Create a file with one URL per line:

cat > urls.txt << EOF
https://example.com/page1
https://example.com/page2
https://x.com/user/status/123
EOF

jina read --file urls.txt --output markdown

Project structure

cli/
├── main.go              # Root command
├── read.go              # read command
├── search.go            # search command
├── config.go            # config command
└── pkg/
    ├── api/client.go    # Jina API HTTP client
    ├── config/          # Config file management
    └── output/          # JSON/Markdown formatter

Implementation notes

  • Go 1.24+ required
  • Zero dependencies except Cobra
  • Single binary distribution
  • Config stored as simple key=value format (no YAML library dependency)

For API details: See cli/pkg/api/client.go

how to use jina-cli

How to use jina-cli on Cursor

AI-first code editor with Composer

1

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 jina-cli
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/geekjourneyx/jina-cli --skill jina-cli

The skills CLI fetches jina-cli from GitHub repository geekjourneyx/jina-cli and configures it for Cursor.

3

Select 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
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/jina-cli

Reload or restart Cursor to activate jina-cli. Access the skill through slash commands (e.g., /jina-cli) 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

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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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.667 reviews
  • Soo Thompson· Dec 24, 2024

    jina-cli is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Pratham Ware· Dec 20, 2024

    Useful defaults in jina-cli — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Chinedu Okafor· Dec 20, 2024

    Solid pick for teams standardizing on skills: jina-cli is focused, and the summary matches what you get after install.

  • Kabir Dixit· Dec 12, 2024

    I recommend jina-cli for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Omar Lopez· Dec 8, 2024

    jina-cli fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Benjamin Ghosh· Nov 27, 2024

    jina-cli has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Omar Ndlovu· Nov 15, 2024

    jina-cli reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Tariq Gupta· Nov 11, 2024

    We added jina-cli from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Soo Robinson· Oct 18, 2024

    Solid pick for teams standardizing on skills: jina-cli is focused, and the summary matches what you get after install.

  • Charlotte Robinson· Oct 6, 2024

    Registry listing for jina-cli matched our evaluation — installs cleanly and behaves as described in the markdown.

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