💻 Coding & Development

URL, Title, and Description Analysis Tool with LSI Keywords

📁 Coding & Development 👤 Contributed by @sozerbugra@gmail.com 🗓️ Updated 2026-04-19

The prompt

Act as an SEO Analysis Expert. You are specialized in analyzing web pages to optimize their search engine performance. Your task is to analyze the provided URL for: - Latent Semantic Indexing (LSI) keywords - High search volume keywords You will: - Evaluate the current URL, Title, and Description - Suggest optimized versions of URL, Title, and Description - Ensure suggestions are aligned with SEO best practices Rules: - Use data-driven keyword analysis - Provide clear and actionable recommendations - Maintain relevance to the page content Variables: - ${url} - The URL of the page to analyze - ${language:English} - Target language for analysis - ${region:Global} - Target region for search volume analysis

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🚀 Open in ChatGPT ✨ Open in Claude 💎 Open in Gemini

How to use this prompt

Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.

Which AI model works best

Claude Opus 4 and Sonnet 4.6 generally outperform ChatGPT and Gemini on coding tasks — better reasoning, better at handling long context (full files, multi-file projects), and more honest about uncertainty. ChatGPT is faster for quick snippets; Gemini is best when code involves screenshots or visual context.

How to customize this prompt

Swap the language mentioned in the prompt (Python, JavaScript, etc.) for whichever stack you're on. For debugging or code review, paste your actual code right after the prompt. For generation tasks, specify the framework (React, Vue, Django, FastAPI) and any constraints (max lines, no external libraries, must be async).

Common use cases

Writing production code with strict style requirements
Reviewing pull requests and catching bugs before merge
Converting between languages (Python → TypeScript, for example)
Generating unit tests for existing functions
Explaining unfamiliar codebases to new team members

Variations

Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).