- Visibility16
- Citations1
- Sentiment50
- Site quality73
- AI readiness36
AI assistants name CNX Resources in 6.7% of answers, which is more often than the typical company in the energy sector. Its overall score is 31 out of 100, ranking 1,129th of 2,047 companies. The CNX Resources website passes 5 of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the energy market: none named CNX Resources. 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, CNX Resources 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
“Which regions in the US lead in ultra-low carbon natural gas development and technology?”
The Appalachian region and the Permian Basin in West Texas appear to lead U.S. ultra-low carbon natural gas development and related technology, with the Rocky Mountain regions also emerging as important centers for low-emissions gas and adjacent technology deployment.
Appalachia is explicitly described by CNX as a center for “ultra-low carbon intensive natural gas development, production, midstream, and technology,” with operations centered on the Marcellus and Utica shales in Pennsylvania, Ohio, and West Virginia.
West Texas / Permian Basin is i …
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 DiscoveryNot present
Advertise agent endpoints with SVCB records under _agents.
- 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 31 of 100 · 97% of checks could run · checked on October 5, 2026 · www.cnx.com · 2,047 companies scanned
5 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%
- Not metHTTP 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.
- GPTBotallowed
- ClaudeBotallowed
- Anthropic-AIallowed
- Google-Extendedallowed
- Applebot-Extendedallowed
- Meta-ExternalAgentallowed
- FacebookBotallowed
- Bytespiderallowed
- CCBotallowed
- Diffbotallowed
- Omgilibotallowed
- OAI-SearchBotallowed
- Claude-SearchBotallowed
- PerplexityBotallowed
- Applebotallowed
- Amazonbotallowed
- YouBotallowed
- ChatGPT-Userallowed
- Claude-Userallowed
- Perplexity-Userallowed
- DuckAssistBotallowed
- MistralAI-Userallowed
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.
- What are alternatives to low-carbon natural gas for companies aiming to decarbonize their operations?
- Which regions in the US lead in ultra-low carbon natural gas development and technology?
- Are low-carbon natural gas solutions a cost-effective choice for large-scale manufacturing facilities looking to reduce emissions?
- Is it worth investing in ultra-low carbon shale gas projects for long-term energy sector returns?
- What challenges can arise when switching an industrial operation to low emission natural gas sources?
- How does renewable natural gas compare to shale-based low-carbon natural gas in terms of lifecycle emissions?
- What are the main differences between conventional and unconventional natural gas extraction for sustainability-focused buyers?
- How can low-carbon shale gas contribute to decarbonizing power generation in the United States?
- What are the best low-carbon natural gas producers in the United States for environmentally conscious investors?
- How do long-term contracts impact the cost of sustainable shale gas supply for utility companies?
- How do you address methane leak risks in low-carbon natural gas production facilities?
- What price range should energy buyers expect for low-carbon intensity natural gas compared to conventional gas?
- What sustainable energy technologies are emerging as competition to low-emission natural gas in manufacturing?
- How does shale gas from the Marcellus formation compare to shale gas from the Permian Basin in terms of carbon intensity?
- What are the most significant industrial uses for ultra-low carbon natural gas in Appalachia?
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/cnx.com"><img src="https://aeo-audit.rezolve.com/us/badges/cnx.com.svg" alt="Overall score 31 of 100, US AI Visibility Study 2026" width="280" height="64"></a>