Overall AI readiness score
A combined result across all audit signals.
Average
AI readiness audit: 10/10/2026Public technical data
Overall AI readiness assessment
How ready buildorskip.dev is for AI systems
Build or Skip is a legitimate product research tool. Its llms.txt is accessible, valid, and consistent with the website. No content policy issues found.
Audit context
llms.txt is accessible and contains 251 tokens. An expanded llms-full.txt is also available with 469 tokens, giving agents more direct context. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.
robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 1. No Schema.org type was detected on the homepage. 0 OpenGraph tags were found and markup completeness is 0%, leaving more entity interpretation to crawlers.
The mobile Lighthouse profile adds Performance 79/100, Accessibility 100/100, Best Practices 96/100, SEO 92/100, and experimental Agentic Browsing 67/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.
Confirmed strengths
- Accessible llms.txt
- Expanded llms-full.txt
- 1 sitemap declaration
Priority improvements
- 1Add JSON-LD for the organisation, website, and core entities.
- 2Complete OpenGraph and canonical homepage metadata.
- 3Reduce mobile rendering delay and main-thread work.
llms.txt tokens251
llms-full.txt tokens469
ai.txt
sitemap.xml
Google Lighthouse technical profile
A mobile Lighthouse measurement. Google’s experimental Agentic Browsing category is explained separately and does not replace the broader llmsmap AI-readiness score.
79
Performance
100
Accessibility
96
Best Practices
92
Technical SEO
67
Agentic Browsing
What these results mean
Mobile performance is 79/100, with the largest visible content block appearing in 4.1 s and the browser main thread blocked for 160 ms. Layout shift was 0.021. The main thread is where the browser runs JavaScript, calculates layout, and paints the page; long work there delays both user input and browser-agent actions.
Accessibility scored 100/100, Best Practices 96/100, and technical SEO 92/100. The experimental Agentic Browsing category scored 67/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.
1
Free the main thread and accelerate the first view
Split long JavaScript tasks, defer non-critical scripts and styles, and shorten blocking request chains. This helps the primary content appear sooner and makes controls usable earlier.
2
Reduce code that loads without helping the page
Remove unused CSS and JavaScript, load heavy widgets on demand, and limit third-party scripts. Less code means less parsing and background work on the device.
3
Optimise images and their loading order
Serve correctly sized modern formats, prioritise the primary visual, and lazy-load content below the first viewport.
4
Reduce network delay
Improve server response time, remove unnecessary redirects and repeat downloads, and use compression, caching, and selective preconnect hints.
FCP1.4 s
First content
LCP4.1 s
Main content
CLS0.021
Layout stability
TBT160 ms
Blocking time
SI6.4 s
Visual speed
Metric glossary
- FCP · First content
- When the first text or image appeared on screen.
- LCP · Main content
- When the largest visible element in the first viewport rendered.
- CLS · Layout stability
- How much content shifted unexpectedly while loading; lower is better.
- TBT · Blocking time
- How long the browser main thread could not respond quickly to input.
- SI · Visual speed
- How quickly the visible viewport filled with content.
10/10/2026Lighthouse 13.5.0Mobile profile
AI readiness checks
Machine-readable files, crawler policy, discovery, and homepage markup.
ai.txt
ai.txt file was not found
Sitemap in robots.txt1
1 sitemap found
Schema.org (JSON-LD)
Schema.org markup was not found on the homepage
OpenGraph
OpenGraph tags were not found on the homepage
AI bot access
Based on robots.txt analysis
GPTBotNot mentioned
OAI-SearchBotNot mentioned
ChatGPT-UserNot mentioned
Google-ExtendedNot mentioned
ClaudeBotNot mentioned
Claude-SearchBotNot mentioned
Claude-UserNot mentioned
BytespiderNot mentioned
CCBotNot mentioned
PerplexityBotNot mentioned
Perplexity-UserNot mentioned
Sitemaps
Declared discovery routes for crawlers and agents.
# Build or Skip > Find products already making money before you build. Build or Skip is a product research and market validation tool for builders, indie hackers, and SaaS teams. It helps users discover products with estimated order momentum before committing to a new idea. ## Key URLs - Homepage: https://buildorskip.dev/ - English homepage: https://buildorskip.dev/en/ - Pricing: https://buildorskip.dev/pricing - GitHub repository: https://github.com/sunnywanggit/build-or-skip ## Product focus - Startup idea validation - Product research - Market validation - SaaS idea research - Product opportunity research - Estimated orders and order growth signals - Builder tools and product discovery ## Summary Build or Skip ranks candidate products by estimated monthly orders, growth, and repeat activity so users can decide what to build, what to watch, and what to skip before investing months into an unproven idea. ## More detail - Full LLM context: https://buildorskip.dev/llms-full.txt
Share or continue the analysis
Share this audit
Discuss with AI
Added 10/10/2026
Similar sites in the directory
Sites with a close AI-readiness score — compare how they set up llms.txt and markup.