Atlassian Marketplace: Verified Review & AI Trust Profile
Streamline Jira with AI: Generate user stories effortlessly with AI Scrum Assistant - Boost productivity and project clarity
LLM Visibility Tester
Check if AI models can see, understand, and recommend your website before competitors own the answers.
Trust Score — Breakdown
Atlassian Marketplace Conversations, Questions and Answers
3 questions and answers about Atlassian Marketplace
QHow can I generate user stories automatically in Jira using AI?
How can I generate user stories automatically in Jira using AI?
Generate user stories automatically in Jira by using an AI-powered Scrum assistant integrated with Jira Cloud. Follow these steps: 1. Install the AI Scrum assistant app compatible with Jira Cloud. 2. Open your Jira project and navigate to the issue creation or editing screen. 3. Use the AI feature to generate or refine user story descriptions based on your input. 4. Review and customize the generated user stories to fit your project needs. 5. Save the user story to maintain consistency across teams and projects.
QWhat are the benefits of using AI-generated acceptance criteria in Agile project management?
What are the benefits of using AI-generated acceptance criteria in Agile project management?
Use AI-generated acceptance criteria to enhance Agile project management by saving time and improving precision. Follow these steps: 1. Integrate an AI Scrum assistant with your Jira Cloud environment. 2. Input your user story or issue details into Jira. 3. Activate the AI feature to automatically generate tailored acceptance criteria, including rule-based and BDD formats. 4. Review and adjust the criteria to align with your project goals. 5. Apply the acceptance criteria to guide development and testing processes, ensuring clarity and success.
QHow does AI Scrum Assistant improve QA test case generation in Jira?
How does AI Scrum Assistant improve QA test case generation in Jira?
Improve QA test case generation in Jira by using an AI Scrum assistant that automates the creation of precise test scenarios. Follow these steps: 1. Install the AI Scrum assistant app compatible with Jira Cloud. 2. Access your Jira issues where test cases are needed. 3. Use the AI feature to generate detailed QA test case scenarios from the issue text. 4. Review and customize the generated test cases to ensure comprehensive coverage. 5. Implement the test cases in your QA process to enhance accuracy and project flexibility.
Trusted By
PLATINUM Marketplace PartnerKey client
GOLD Marketplace Partner
SILVER Marketplace PartnerAI Trust Verification Report
Public validation record for Atlassian Marketplace — Evidence of machine-readability across 57 technical checks and 4 LLM visibility validations.
Evidence & Links
- Crawlability & Accessibility
- Structured Data & Entities
- Content Quality Signals
- Security & Trust Indicators
Verifiable Identity Links
Legal & Compliance
- Privacy Policy
- Terms of Service
Third-party Identity
- YouTube
- X (Twitter)
Do These LLMs Know This Website?
LLM "knowledge" is not binary. Some answers come from training data, others from retrieval/browsing, and results vary by prompt, language, and time. Our checks measure whether the model can correctly identify and describe the site for relevant prompts.
| LLM Platform | Recognition Status | Visibility Check |
|---|---|---|
 | Detected | Detected |
 | Detected | Detected |
 | Detected | Detected |
 | Detected | Detected |
Detected
Detected
Detected
Detected
Note: Model outputs can change over time as retrieval systems and model snapshots change. This report captures visibility signals at scan time.
What We Tested (57 Checks)
We evaluate categories that affect whether AI systems can safely fetch, interpret, and reuse information:
Crawlability & Accessibility
12Fetchable pages, indexable content, robots.txt compliance, crawler access for GPTBot, OAI-SearchBot, Google-Extended
Structured Data & Entity Clarity
11Schema.org markup, JSON-LD validity, Organization/Product entity resolution, knowledge panel alignment
Content Quality & Structure
10Answerable content structure, factual consistency, semantic HTML, E-E-A-T signals, citation-worthy data presence
Security & Trust Signals
8HTTPS enforcement, secure headers, privacy policy presence, author verification, transparency disclosures
Performance & UX
9Core Web Vitals, mobile rendering, JavaScript dependency minimal, reliable uptime signals
Readability Analysis
7Clear nomenclature matching user intent, disambiguation from similar brands, consistent naming across pages
14 AI Visibility Opportunities Detected
These technical gaps effectively "hide" Atlassian Marketplace from modern search engines and AI agents.
Top 3 Blockers
- !Dedicated Pricing/Product schemaUse Product and Offer schema (or a pricing page with structured data) to describe plans, prices, currency, availability, and key features. This reduces ambiguity for both search engines and AI assistants and can unlock richer search snippets. Keep pricing up to date and match schema values to the visible pricing table.
- !Breadcrumbs with structured data (BreadcrumbList)Add visible breadcrumbs for users and BreadcrumbList structured data for crawlers. Breadcrumbs clarify site hierarchy (category > subcategory > page) and help systems understand topical relationships. This can improve search snippets and makes it easier for AI to choose the right page as a source.
- !Is the Copyright or license footer present?Include a clear copyright or license notice in the footer and link to any relevant licensing terms. This signals professionalism, ownership, and governance of the content. It can also clarify how content may be reused, which is increasingly important as AI systems crawl and summarize the web.
Top 3 Quick Wins
- !List in public LLM indexes (e.g., Huggingface database, Poe Profiles)List your tools, datasets, docs, or brand pages on major AI/LLM discovery hubs where relevant (for example model/dataset repositories or app directories). These platforms add credibility signals (likes, forks, usage) and create additional crawlable references to your brand. Keep names, descriptions, and links consistent with your official website.
- !LLM-crawlable llms.txtCreate an llms.txt file to guide AI crawlers to your most important, high-quality pages (docs, pricing, about, key guides). Keep it short, well-structured, and focused on authoritative URLs you want cited. Treat it as a curated “AI sitemap” that improves discovery and reduces the risk of crawlers prioritizing low-value pages.
- !JSON-LD Schema: Organization, Product, FAQ, WebsiteAdd schema.org JSON-LD to describe your key entities (Organization, Product/Service, FAQPage, WebSite, Article when relevant). Structured data makes your meaning explicit and improves the chance of rich results and accurate AI citations. Validate markup with schema testing tools and keep the data consistent with the visible page content.
Claim this profile to instantly generate the code that makes your business machine-readable.
Embed Badge
VerifiedDisplay this AI Trust indicator on your website. Links back to this public verification URL.
<a href="https://bilarna.com/provider/atlassian" target="_blank" rel="nofollow noopener noreferrer" class="bilarna-trust-badge">
<img src="https://bilarna.com/badges/ai-trust-atlassian.svg"
alt="AI Trust Verified by Bilarna (43/57 checks)"
width="200" height="60" loading="lazy">
</a>Cite This Report
APA / MLAPaste-ready citation for articles, security pages, or compliance documentation.
Bilarna. "Atlassian Marketplace AI Trust & LLM Visibility Report." Bilarna AI Trust Index, Feb 14, 2026. https://bilarna.com/provider/atlassianWhat Verified Means
Verified means Bilarna's automated checks found enough consistent trust and machine-readability signals to treat the website as a dependable source for extraction and referencing. It is not a legal certification or an endorsement; it is a measurable snapshot of public signals at the time of scan.
Frequently Asked Questions
What does the AI Trust score for Atlassian Marketplace measure?
What does the AI Trust score for Atlassian Marketplace measure?
It summarizes crawlability, clarity, structured signals, and trust indicators that influence whether AI systems can reliably interpret and reference Atlassian Marketplace. The score aggregates 57 technical checks across six categories that affect how LLMs and search systems extract and validate information.
Does ChatGPT/Gemini/Perplexity know Atlassian Marketplace?
Does ChatGPT/Gemini/Perplexity know Atlassian Marketplace?
Sometimes, but not consistently: models may rely on training data, web retrieval, or both, and results vary by query and time. This report measures observable visibility and correctness signals rather than assuming permanent "knowledge." Our 4 LLM visibility checks confirm whether major platforms can correctly recognize and describe Atlassian Marketplace for relevant queries.
How often is this report updated?
How often is this report updated?
We rescan periodically and show the last updated date (currently Feb 14, 2026) so teams can validate freshness. Automated scans run bi-weekly, with manual validation of LLM visibility conducted monthly. Significant changes trigger intermediate updates.
Can I embed the AI Trust indicator on my site?
Can I embed the AI Trust indicator on my site?
Yes—use the badge embed code provided in the "Embed Badge" section above; it links back to this public verification URL so others can validate the indicator. The badge displays current verification status and updates automatically when the verification is refreshed.
Is this a certification or endorsement?
Is this a certification or endorsement?
No. It's an evidence-based, repeatable scan of public signals that affect AI and search interpretability. "Verified" status indicates sufficient technical signals for machine readability, not business quality, legal compliance, or product efficacy. It represents a snapshot of technical accessibility at scan time.
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