- Visibility10
- Citations0
- Sentiment70
- Site quality73
- AI readiness43
AI assistants name PBF Energy in 6.7% of answers, which is about twice as often as the typical company in the energy sector. Its overall score is 33 out of 100, ranking it 985th of 2,047 companies. The website passes 6 out of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the energy market: none named PBF Energy. AI assistants named it in 4 of 60 answers (6.7%). The typical energy company is named in 3.3% of answers. By how often it is named, PBF Energy ranks 36 of 109 in its sector.
Every dot is a company in the study. Hover one to see it; click to open its report.
This companySame sectorEvery other companyNever named
Five parts, each scored out of 100.
How often AI assistants name the company
How often AI uses the company's own website as a source
How positively AI describes the company
How well built the website's own pages are
How easily AI tools can read and use the website
Visibility is calculated from the answers on this page. How the score is built.
109 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“How do operational costs vary among different types of U.S. refining facilities?”
Operational costs vary materially by refinery type, complexity, and product slate. In the U.S., simple-to-moderate refiners tend to sit on the low end of the cost curve, while more complex, harder-to-run, or regulation-constrained facilities often spend several dollars more per barrel to keep plants operating and maintained.
A recent cross-refiner comparison shows this spread clearly:
Refiner type / company group · Approx. operating + turnaround cost per barrel
Low-cost refiners such as Phillips 66 and Valero · about $5.80/bbl
Mid-cost refiners …
The AI’s answer as we received it, shortened and not checked for accuracy.
How the mentions in these answers were split between this company and its rivals
Answers naming it, out of answers received
What this website publishes for an AI agent to read, use and buy from, on a scale of six levels.
- 0
- 1
- 2
- 3
- 4
- 5
Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.
- Content Signals
Show every check, for your technical teamHide the checks
- study: 92.0%robots.txtPassed
A valid robots.txt with crawl rules at the site root.
- study: 86.8%SitemapPassed
An XML sitemap listing the pages, ideally referenced from robots.txt.
- study: 0.3%Link headersNot met
Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.
- study: 5.5%DNS for AI DiscoveryPassed
SVCB or HTTPS records under _agents that advertise agent endpoints.
- study: 1.9%Markdown negotiationNot met
Return a markdown version when asked with Accept: text/markdown, for example at the CDN.
- study: 25.1%llms.txtNot met
Publish an llms.txt with a short summary and the key links.
- study: 93.4%AI bot rulesPartly met
Add explicit robots.txt groups for the main AI crawlers.
- study: 1.4%Content SignalsNot met
Add a Content-Signal line for search, ai-input and ai-train to robots.txt.
- study: 0.2%Web Bot AuthNot present
Only relevant if you run your own agents or crawlers: publish a signing key directory.
- study: 0.3%API CatalogNot met
List public APIs in a linkset at /.well-known/api-catalog.
- study: 11.8%OAuth discoveryPartly met
Publish OpenID Connect or OAuth server metadata under /.well-known.
- study: 10.3%OAuth Protected ResourcePassed
Metadata telling agents which authorization server to use.
- study: 0.0%auth.mdNot met
Publish an auth.md describing how agents sign in.
- study: 0.2%MCP Server CardNot met
Offer an MCP server and publish its server card under /.well-known.
- study: 0.1%A2A Agent CardNot met
Publish an agent card at /.well-known/agent-card.json.
- study: 0.2%Agent SkillsNot met
Publish a skills index with the main tasks agents can do.
- study: 33.7%WebMCPCould not check
Register key actions such as search or cart as WebMCP tools.
- study: 0.1%ARD manifestNot met
Publish an ai-catalog.json listing every agent interface.
Score 33 of 100 · 97% of checks could run · checked on October 5, 2026 · www.pbfenergy.com · 2,047 companies scanned
6 of 14 passed. This list is for your technical team. The percentage is how many companies in the study pass each check.
These 14 checks ran during the audit and are what the AI readiness part of the overall score counts. The scan above ran later and is stricter on Link headers and Markdown, so a check can pass here and not there.
Show the 14 checksHide them
- Passedrobots.txt publishedstudy: 85.0%
- PassedXML sitemapstudy: 73.2%
- PassedHTTP Link headers (RFC 8288)study: 29.0%
- Not metMarkdown content negotiationstudy: 8.3%
- Not metllms.txt publishedstudy: 21.7%
- PassedToken budget (page weight)study: 95.2%
- Not metExplicit AI bot rulesstudy: 13.0%
- Not metAPI Catalog (.well-known/api-catalog)study: 0.2%
- PassedOAuth Authorization Server discoverystudy: 10.1%
- PassedOAuth Protected Resource discoverystudy: 9.3%
- Not metMCP Server Cardstudy: 0.0%
- Not metA2A Agent Cardstudy: 0.0%
- Not metWebMCP toolsstudy: 4.2%
- Not metAgent Skills declaredstudy: 0.0%
This website sets no rules for any AI crawler by name, like 84% of the websites whose rules we could read. Every AI crawler follows its general rules.
- GPTBotpartly
- ClaudeBotpartly
- Anthropic-AIpartly
- Google-Extendedpartly
- Applebot-Extendedpartly
- Meta-ExternalAgentpartly
- FacebookBotpartly
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBotpartly
- Claude-SearchBotpartly
- PerplexityBotpartly
- Applebotpartly
- Amazonbotpartly
- YouBotpartly
- ChatGPT-Userpartly
- Claude-Userpartly
- Perplexity-Userpartly
- DuckAssistBotpartly
- MistralAI-Userpartly
Read from the website’s own rules file (robots.txt). An asterisk marks a crawler the file names. The rest follow its general rules. “Partly” means only some pages are blocked.
How many times each website was listed as a source in these answers
In the study as US-listed.
- How does hydrocracking compare to catalytic cracking in modern petroleum refining?
- Is investing in state-of-the-art refining facilities worth the higher upfront costs?
- What are the best alternative energy sources for large-scale industrial operations?
- Alternatives to fossil fuel-based refining for sustainable industrial energy solutions
- Best practices in refinery workforce training and development in U.S. energy operations
- Alternatives to traditional petroleum refining for meeting industrial energy needs
- How do operational costs vary among different types of U.S. refining facilities?
- What factors impact the pricing of refined petroleum products in the United States?
- Examples of successful workforce development programs in refining operations
- What are the top-rated petroleum refining companies in the United States for reliable energy operations?
- Common safety challenges in petroleum refining and how to address them
- How do large-scale industrial clients benefit from advanced refinery expertise?
- How can U.S. refinery operators enhance reliability in their energy operations?
- Benefits of choosing an energy partner with a comprehensive preventive maintenance program
- Refined petroleum products vs renewable diesel: which is more efficient for industrial clients?
Columns, left to right: OpenAI, Claude, Perplexity, Gemini. The AI assistants often disagree. Across the study, on 40% of the questions where a company is named, only one of the four names it.
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<a href="https://aeo-audit.rezolve.com/us/pbfenergy.com"><img src="https://aeo-audit.rezolve.com/us/badges/pbfenergy.com.svg" alt="Overall score 33 of 100, US AI Visibility Study 2026" width="280" height="64"></a>