Robotstxt Generator
Generate a robots.txt file with crawl directives for search engine bots. Enter values for instant results with step-by-step formulas.
Calculator
Adjust values & calculaterobots.txt
User-agent: * Disallow: /admin/ Disallow: /private/ Disallow: /tmp/
Formula
A robots.txt file uses directives to instruct crawlers. User-agent specifies which bot, Disallow blocks paths, Allow overrides within blocked directories, Crawl-delay sets request intervals, and Sitemap points to your XML sitemap.
Last reviewed: December 2025
Worked Examples
Example 1: Standard Business Website
Example 2: Blog Blocking AI Crawlers
Background & Theory
The Robots.txt Generator applies the following established principles and formulas. Search engine optimisation and digital marketing performance is quantified through a hierarchy of interconnected metrics. Click-through rate (CTR) divides the number of clicks on a link by the number of times it was shown (impressions), expressing how compelling a headline, ad, or meta description is at a given position. Industry average organic CTR for the top Google result sits around 28 to 35 percent, declining sharply with rank. Cost-per-click (CPC) is the average amount paid each time a user clicks a paid advertisement, calculated by dividing total ad spend by total clicks. Return on ad spend (ROAS) divides total revenue attributed to advertising by total ad spend; a ROAS of 4 means $4 in revenue for every $1 spent. Conversion rate divides completed goal actions (purchases, sign-ups, downloads) by total sessions or unique visitors, bridging traffic metrics to business outcomes. Keyword difficulty scores (typically 0 to 100) estimate how competitive it would be to rank organically for a given search term, based on the authority of pages currently ranking in the top results. PageRank, the algorithm Google was originally built on, modelled the web as a directed graph and assigned each page an authority score proportional to the number and quality of inbound links, treating a link as a vote of confidence weighted by the linking page's own authority. The Flesch Reading Ease formula scores text legibility on a 0 to 100 scale using sentence length and syllable count per word. Higher scores indicate easier reading; most consumer-oriented web content targets scores above 60. Bounce rate measures the percentage of sessions in which a user leaves without triggering a second page view, though its interpretation depends heavily on page purpose. Email open rate benchmarks vary significantly by industry, averaging around 20 to 25 percent across sectors. Social media engagement rate divides total interactions (likes, comments, shares) by total reach or follower count, assessing content resonance beyond simple impression counts.
History
The history behind the Robots.txt Generator traces back through the following developments. Before algorithmic search engines, web navigation relied on manually curated directories maintained by human editors. Yahoo launched its categorised directory in 1994 and briefly dominated web discovery by organising sites into a hierarchical taxonomy. Early automated search engines including AltaVista and Excite ranked pages using keyword frequency in on-page content, which immediately spawned keyword stuffing as the first widespread manipulation tactic: publishers repeated target phrases hundreds of times, sometimes rendered in white text on a white background to hide them from readers while remaining visible to crawlers. Google's founding in 1998 by Larry Page and Sergey Brin at Stanford introduced PageRank, a link-graph authority algorithm that shifted ranking signals away from easily gamed on-page text toward the harder-to-fabricate structure of inbound links. This dramatically improved result quality and positioned Google as the dominant search engine within three years of launch. The growing commercial value of first-page rankings created a professional SEO industry that reverse-engineered ranking signals, built link farms, and pursued aggressive anchor text optimisation. Google responded to systematic manipulation with major named algorithm updates: Panda in 2011 penalised low-quality, thin, and duplicate content; Penguin in 2012 targeted unnatural link patterns and link schemes; and Hummingbird in 2013 introduced deep semantic parsing to match query intent rather than literal keyword strings. These updates collectively shifted SEO best practice toward genuine content quality, topical depth, and user experience signals. Facebook launched its self-service advertising platform in 2007, enabling granular demographic, interest, and behavioural targeting at scale for the first time. Social media marketing matured into a distinct professional discipline through the 2010s. Google formalised mobile-first indexing in 2016 and made Core Web Vitals official ranking signals in 2021. From 2023 onward, AI Overviews began surfacing synthesised answers atop search results, creating a zero-click environment that fundamentally challenged traffic-dependent content business models.
Frequently Asked Questions
Sources & References
Formula
User-agent → Disallow/Allow → Crawl-delay → Sitemap
A robots.txt file uses directives to instruct crawlers. User-agent specifies which bot, Disallow blocks paths, Allow overrides within blocked directories, Crawl-delay sets request intervals, and Sitemap points to your XML sitemap.
Worked Examples
Example 1: Standard Business Website
Problem: Generate a robots.txt for a business site that blocks admin, login, and staging areas while providing the sitemap location.
Solution: User-agent: *\nDisallow: /admin/\nDisallow: /login/\nDisallow: /staging/\nDisallow: /api/\nAllow: /api/public/\n\nSitemap: https://example.com/sitemap.xml
Result: Clean robots.txt with 4 disallow rules, 1 allow override, and sitemap
Example 2: Blog Blocking AI Crawlers
Problem: Create a robots.txt for a blog that allows all search engines but blocks AI training crawlers.
Solution: User-agent: *\nDisallow: /draft/\nDisallow: /preview/\n\nUser-agent: GPTBot\nDisallow: /\n\nUser-agent: Google-Extended\nDisallow: /\n\nUser-agent: CCBot\nDisallow: /\n\nSitemap: https://blog.example.com/sitemap.xml
Result: Search engines can crawl freely; AI training bots are fully blocked
Frequently Asked Questions
How do I interpret the result?
Results are displayed with a label and unit to help you understand the output. Many calculators include a short explanation or classification below the result (for example, a BMI category or risk level). Refer to the worked examples section on this page for real-world context.
Is my data stored or sent to a server?
No. All calculations run entirely in your browser using JavaScript. No data you enter is ever transmitted to any server or stored anywhere. Your inputs remain completely private.
How do I get the most accurate result?
Enter values as precisely as possible using the correct units for each field. Check that you have selected the right unit (e.g. kilograms vs pounds, meters vs feet) before calculating. Rounding inputs early can reduce output precision.
Why might my result differ from another tool or reference?
Differences typically arise from rounding conventions, the specific version of a formula (for example, simple vs compound interest), or unit inconsistencies between inputs. Check that both tools are using the same formula variant and the same units. The References section links to the authoritative source behind the formula used here.
Can I use Robotstxt Generator on a mobile device?
Yes. All calculators on NovaCalculator are fully responsive and work on smartphones, tablets, and desktops. The layout adapts automatically to your screen size.
Can I use the results for professional or academic purposes?
You may use the results for reference and educational purposes. For professional reports, academic papers, or critical decisions, we recommend verifying outputs against peer-reviewed sources or consulting a qualified expert in the relevant field.
References
Reviewed by Daniel Agrici, Founder & Lead Developer · Editorial policy