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Intrepid Potash

intrepidpotash.com · Unclassified · IPI

Ranked 1,800 of 2,047 companies in the study

25Overall score
  • Visibility4
  • Citations0
  • Sentiment50
  • Site quality67
  • AI readiness29
What this means for Intrepid Potash

AI assistants rarely name Intrepid Potash in their answers, mentioning the company in just 1 of 60 responses. Its overall score is 25 out of 100, ranking 1,800th of 2,047 companies. The company's website passes 4 out of 14 technical checks for readiness with AI tools.

We asked 15 unbranded questions about its market: none named Intrepid Potash. AI assistants named it in 1 of 60 answers (1.7%). The typical company in its group is named in 3.3% of answers. By how often it is named, Intrepid Potash ranks 35 of 61 in its sector.

Named fewer than three times in total. Read this as a sign that AI assistants rarely bring this company up, not as an exact comparison with its rivals.

Named by AI in
1.7%
1 of 60 answers
Share of mentions
6.7%
compared with 5 rivals
AI readiness
4/14
technical checks passed. Typical for its sector: 3
Rank in its sector
46 of 61
by overall score, where the typical company scores 29
How Intrepid Potash compares with all 2,047 companies

Every dot is a company in the study. Hover one to see it; click to open its report.

This companySame sectorEvery other companyNever named

What makes up the score

Five parts, each scored out of 100.

Visibility
4

How often AI assistants name the company

Citations
0

How often AI uses the company's own website as a source

Sentiment
50

How positively AI describes the company

Site quality
67

How well built the website's own pages are

AI readiness
29

How easily AI tools can read and use the website

Visibility is calculated from the answers on this page. How the score is built.

Compared with its group

61 companies in this sector. The line on each bar is the typical company.

Overall score25
Ranks 46 of 61. Typical company: 29
Named in answers2%
Ranks 35 of 61. Typical company: 3%
AI readiness29
Ranks 15 of 61. Typical company: 21
What Perplexity actually said

An answer that names the company

“What are the best essential minerals suppliers for large-scale agriculture in the US?”

For large-scale agriculture in the U.S., the strongest essential-minerals suppliers are usually the major fertilizer and plant-nutrition producers with large domestic production and distribution networks. Based on the available evidence, the clearest top names are Nutrien, Mosaic, Compass Minerals, and Intrepid Potash.

Nutrien — one of the largest integrated suppliers of potash, nitrogen, and phosphate products, with a stated output/distribution network of 27.5 million tonnes.

The Mosaic Company — a major U.S. fertilizer producer …

The AI’s answer as we received it, shortened and not checked for accuracy.

Also named
Nutrien3Compass Minerals3
Share of mentions

How the mentions in these answers were split between this company and its rivals

Mosaic Company
30.0%
Compass Minerals
30.0%
Nutrien
30.0%
Intrepid Potash
10.0%
K+S Minerals and Agriculture (K+S North America)
0.0%
SaltWorks
0.0%
Which AI assistants named the company

Answers naming it, out of answers received

Perplexity
1/15
Gemini
0/15
Claude
0/15
OpenAI
0/15
Ready for AI agents

What this website publishes for an AI agent to read, use and buy from, on a scale of six levels.

  1. 0
  2. 1
  3. 2
  4. 3
  5. 4
  6. 5

Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.

To reach level 2:
  • Content Signals
Show every check, for your technical team
Discoverability
77 of 100
  • robots.txtPassed

    A valid robots.txt with crawl rules at the site root.

    study: 92.0%
  • SitemapPassed

    An XML sitemap listing the pages, ideally referenced from robots.txt.

    study: 86.8%
  • Link headersNot met

    Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.

    study: 0.3%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 5.5%
Content accessibility
0 of 100
  • Markdown negotiationNot met

    Return a markdown version when asked with Accept: text/markdown, for example at the CDN.

    study: 1.9%
  • llms.txtNot met

    Publish an llms.txt with a short summary and the key links.

    study: 25.1%
Bot access control
32 of 100
  • AI bot rulesPartly met

    Add explicit robots.txt groups for the main AI crawlers.

    study: 93.4%
  • Content SignalsNot met

    Add a Content-Signal line for search, ai-input and ai-train to robots.txt.

    study: 1.4%
  • Web Bot AuthNot present

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.2%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 0.3%
  • OAuth discoveryNot met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 11.8%
  • OAuth Protected ResourceNot met

    Serve protected resource metadata at /.well-known/oauth-protected-resource.

    study: 10.3%
  • auth.mdNot met

    Publish an auth.md describing how agents sign in.

    study: 0.0%
  • MCP Server CardNot met

    Offer an MCP server and publish its server card under /.well-known.

    study: 0.2%
  • A2A Agent CardNot met

    Publish an agent card at /.well-known/agent-card.json.

    study: 0.1%
  • Agent SkillsNot met

    Publish a skills index with the main tasks agents can do.

    study: 0.2%
  • WebMCPCould not check

    Register key actions such as search or cart as WebMCP tools.

    study: 33.7%
  • ARD manifestNot met

    Publish an ai-catalog.json listing every agent interface.

    study: 0.1%

Score 25 of 100 · 97% of checks could run · checked on October 5, 2026 · www.intrepidpotash.com · 2,047 companies scanned

See how every company did, and how this was measured.

The checks behind the AI readiness score

4 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 checks
Discoverability
  • Passedrobots.txt publishedstudy: 85.0%
  • PassedXML sitemapstudy: 73.2%
  • PassedHTTP Link headers (RFC 8288)study: 29.0%
Content Accessibility
  • Not metMarkdown content negotiationstudy: 8.3%
  • Not metllms.txt publishedstudy: 21.7%
  • PassedToken budget (page weight)study: 95.2%
Bot Access Control
  • Not metExplicit AI bot rulesstudy: 13.0%
API / Auth / MCP
  • Not metAPI Catalog (.well-known/api-catalog)study: 0.2%
  • Not metOAuth Authorization Server discoverystudy: 10.1%
  • Not metOAuth 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%
What AI crawlers may read (robots.txt)

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.

Training AI
  • GPTBotallowed
  • ClaudeBotallowed
  • Anthropic-AIallowed
  • Google-Extendedallowed
  • Applebot-Extendedallowed
  • Meta-ExternalAgentallowed
  • FacebookBotallowed
  • Bytespiderallowed
  • CCBotallowed
  • Diffbotallowed
  • Omgilibotallowed
AI search
  • OAI-SearchBotallowed
  • Claude-SearchBotallowed
  • PerplexityBotallowed
  • Applebotallowed
  • Amazonbotallowed
  • YouBotallowed
Answering questions
  • 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.

Websites the AI used as sources

How many times each website was listed as a source in these answers

pmc.ncbi.nlm.nih.gov
16
icl-growingsolutions.com
12
extension.msstate.edu
11
cropnutrition.com
11
farmonaut.com
9
pda.org.uk
8
extension.umn.edu
8
indexbox.io
8
pubs.usgs.gov
8
imarcgroup.com
7

In the study as US-listed.

Every question, and where the company came up (1 of 15)
QuestionOpenAIClaudePerplexityGemini
  • Potassium chloride vs sulfate of potash for vegetable crops—what are the main differences?
  • Where do US farmers typically source potassium and magnesium for crop production?
  • What role does salt play in animal feed formulations for beef cattle?
  • How can I tell if my hay fields are magnesium deficient?
  • How much does industrial magnesium cost per ton for oil and gas applications?
  • Is it worth paying extra for high purity potash in row crop farming?
  • What are alternatives to conventional mined potash for organic farms?
  • How is potassium used in irrigation and fertigation systems for orchards?
  • How does agricultural grade salt compare with industrial grade salt for livestock use?
  • Why are my corn yields low even after applying potassium-based fertilizers?
  • Are mineral blends with sulfur a good investment for improving forage quality?
  • Are there effective substitutes for sodium chloride in de-icing and industrial applications?
  • What are the best essential minerals suppliers for large-scale agriculture in the US?
  • What factors affect the price of bulk potassium deliveries in the US?
  • Which types of essential minerals are most important for sustainable soil health in US agriculture?
named the companyanswered without naming itdid not answer

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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