What happened: how the Atlassian X-ray was made

The X-ray of Atlassian · the deck · how every X-ray is made · X-ray another name

This page shows what the agents did to make the X-ray of Atlassian, in the order it happened. Every number comes from two files: the raw record of the search (data/xray/atlassian/search/20261107T190857Z.json) and the X-ray itself (data/xray/atlassian/xray.json).

Step 1 of 6

1. The ask

On 7 November 2026 at 19:08 UTC, xray@web-summit.dinis typed one line into the search tool (admin/tools/xray-search.mjs): "Atlassian Rovo agents", as a company. It was not typed at the booth: that path is still being built (WS-194).

The search tool is the orchestrator. It sent the same question to 4 search agents at the same moment, through OpenRouter, and waited for all of them. Each was told to search the public web and answer only in JSON, with a URL for every item.

  1. Perplexity search perplexity/sonar
  2. OpenAI search openai/gpt-5.4-nano:online
  3. Gemini search google/gemini-3.1-flash-lite:online
  4. OpenRouter web search anthropic/claude-haiku-5.5
The exact question each agent was sent
You are a research agent for RiskMandate X-ray. Subject (a company): "Atlassian Rovo agents".
Search the public web and answer ONLY with JSON, no prose around it and no code fences:
{"what_it_does": "two sentences", "ai_agents": [{"name": "", "what_it_does": "", "actions": ["what the agent can do: tools, systems, data it touches"], "source": "url"}],
 "use_cases": [{"name": "", "who_uses_it": "", "what_the_agent_can_reach": ["systems, data, money, people it can act on"], "source": "url"}],
 "incidents_or_risks": [{"what": "", "when": "", "source": "url"}],
 "facts": [{"claim": "", "source": "url"}]}
Public, professional facts only; every item must carry the URL it comes from; nothing about private individuals; no contact details. If you find nothing for a field, give an empty list.

Rebuilt from admin/tools/xray-ask.mjs with this run's subject and kind. The question has not changed since the first run.

Step 2 of 6

2. Each search agent's call

Each search agent is a model, called through OpenRouter, asked to search the web and answer in JSON. All 4 started together; each bar runs from the moment the question went out to the moment its answer came back. The whole fan-out took 28.0 s, the time of the slowest.

Perplexity search6.6 s
OpenAI search21.5 s
Gemini search4.4 s
OpenRouter web search28.0 s

Perplexity search

perplexity/sonar

Time
6.6 s
Tokens in / out
209 / 1,025
Cost
$0.0062
Finished
stop: it finished its answer
URLs given
15 (15 returned as citations, 9 named in its answer)
Items in its answer
16
Leads checked
17: 17 confirmed, 0 not found, 0 unverified

Some of what it said, word for word:

  • Rovo is Atlassian’s AI offering for finding personalized answers, automating tasks, and making smarter decisions using connected organizational context.
  • Rovo is powered by the Teamwork Graph, which maps relationships across people, apps, projects, code, decisions, and assets.
  • Rovo agents are designed to handle specific tasks and automate multi-step work across Atlassian and connected apps.

OpenAI search

openai/gpt-5.4-nano:online

Time
21.5 s
Tokens in / out
17,522 / 2,139
Cost
$0.0352
Finished
stop: it finished its answer
URLs given
9 (0 returned as citations, 9 named in its answer)
Items in its answer
13
Leads checked
14: 12 confirmed, 0 not found, 2 unverified

Some of what it said, word for word:

  • Rovo agents can be accessed in Chat, automation rules, within Jira/Confluence via shortcut commands, and in Studio.
  • Skills are reusable instructions that let Rovo Chat and agents carry out specific work-based actions (e.g., creating work items, drafting status updates, analyzing incident data).
  • Agents can access data from other Atlassian and connected third-party apps depending on their knowledge sources, and they respect user permissions (no cross-site access to unauthorized users).

Gemini search

google/gemini-3.1-flash-lite:online

Time
4.4 s
Tokens in / out
228 / 836
Cost
$0.0567
Finished
stop: it finished its answer
URLs given
4 (0 returned as citations, 4 named in its answer)
Items in its answer
7
Leads checked
9: 7 confirmed, 2 not found, 0 unverified

Some of what it said, word for word:

  • Atlassian Rovo is powered by the 'Teamwork Graph,' which maps relationships across people, apps, projects, and code to provide context-aware AI interactions.
  • Rovo agents are designed to inherit the access permissions of the human user, meaning they can only see and act upon data that the authenticated user is authorized to access.
  • ResearchAgent: An agent capable of conducting multi-source web research and navigating across arbitrary sites to synthesize information.

OpenRouter web search

anthropic/claude-haiku-5.5, with OpenRouter's web search plugin

Time
28.0 s
Tokens in / out
34,750 / 6,038
Cost
$0.0262
Finished
stop: it finished its answer
URLs given
13 (0 returned as citations, 13 named in its answer)
Items in its answer
28
Leads checked
28: 28 confirmed, 0 not found, 0 unverified

Some of what it said, word for word:

  • Rovo agents are described by Atlassian as configurable AI teammates that any team member can call on or create, and they draw on Atlassian apps and connected third-party apps.
  • Agent skills are the actions an agent is allowed to take, such as drafting a Confluence page or sending Slack messages, while knowledge is the data it can reference.
  • Atlassian's documentation says agents can be configured with knowledge sources such as Confluence, Jira, and Google Drive, plus deep research or web search.

"Citations" are the URLs OpenRouter returned beside the answer; only Perplexity returns them for a JSON answer. "Named in its answer" are the URLs inside the JSON. Both are leads: nothing is taken from them until a source is read. "Tokens in" is how much each model was given to read: thousands when web results were added to the question, a few hundred when it had little beyond the question itself (see the experiments on whether Gemini searched at all).

Step 3 of 6

3. From claims to facts

What a model says is a lead. Only what we read on its source reaches the page.

The reading agent turned the 4 answers into 68 leads, each tagged with the model that said it, and looked for each one on a source it read. 64 confirmed, 2 not found, 2 unverified.

confirmednot foundunverified

  • Confirmed: a source we read says it.
  • Not found: we read the source, or looked for one, and it does not say it.
  • Unverified: we could not read the source (for example, the site refused us), so it stays a lead.
AgentLeadsConfirmedNot foundUnverified
Perplexity search171700
OpenAI search141202
Gemini search9720
OpenRouter web search282800
All686422

What did not hold up, and why

ModelWhat the model saidStatusWhy
openaiAdmins can control an agent's knowledge scope, for example unit-wide scope versus specific sites.unverifiedThe cited Atlassian Community discussion returned an empty page; the knowledge sources page (s8) describes builder-chosen custom knowledge, not this admin control.
openaiA Reddit discussion reports a critical cross-user and cross-tenant compromise in Rovo.unverifiedThe Reddit page returned no content; no other source read today reports a cross-tenant failure, and the THN and CSA reports describe exposure bounded by the signed-in user's own access.
geminiEngineering use case reaches source code in Bitbucket or GitHub and incident alerts in Opsgenie.not-foundThe cited Rovo page (s1) mentions pulling context across code but names neither Bitbucket, GitHub nor Opsgenie.
geminiIT service management use case reaches JSM tickets, knowledge base articles, incident history and SLA status.not-foundNot on the cited Rovo page (s1); JSM agents are documented on s5, but SLA status access is not stated anywhere read.

Step 4 of 6

4. The reading agent

A reading agent: a Claude Code sub-agent of xray@web-summit.dinis, one per subject. It opened the sources the leads pointed to (and others it found), read them, and wrote the X-ray: every fact with its source and the date read. It finished at 7 November 2026 at 19:18 UTC.

39sources read
45tool calls
7 min 47 sreading time
204ktokens used

The sources, by kind

own-site9
docs21
press2
filing0
other7
All 39 sources, with the date each was read
IdSourceKindRead
s1Rovo: Unlock organizational knowledge with GenAI | Atlassian, Atlassianown-site2026-11-07
s2Agents | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s3What is Rovo? | Atlassian, Atlassianown-site2026-11-07
s4What are agents? | Rovo Studio | Atlassian Support, Atlassian Supportdocs2026-11-07
s5Out-of-the-box agents | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s6What are skills? | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s7Add tools to Rovo agents | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s8Knowledge sources for Rovo subagents | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s9What's the difference between a skill and tool? | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s10Rovo agent permissions and governance | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s11Understand Rovo agent accounts | Rovo Studio | Atlassian Support, Atlassian Supportdocs2026-11-07
s12Best practices to automate agents safely | Rovo Studio | Atlassian Support, Atlassian Supportdocs2026-11-07
s13Automate Rovo agents | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s14How to configure the Use agent action | Cloud automation | Atlassian Support, Atlassian Supportdocs2026-11-07
s15Collaborate on work items with AI agents | Jira Cloud | Atlassian Support, Atlassian Supportdocs2026-11-07
s16Rovo Chat capabilities | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s17Rovo data, privacy, and usage guidelines | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s18Out-of-the-box third-party MCP agents | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s19Rovo out-of-the-box third-party MCP agents usage guidelines | Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s20Manage web access for Rovo | Atlassian Support, Atlassian Supportdocs2026-11-07
s21Manage Rovo access | Atlassian Support, Atlassian Supportdocs2026-11-07
s22Govern external AI access | Rovo MCP server setup guide | Learning - Atlassian Community, Atlassian Community (Atlassian Learning)docs2026-11-07
s23AI Transparency Notes | Atlassian, Atlassianown-site2026-11-07
s24Rovo Plans and Trial | Atlassian, Atlassianown-site2026-11-07
s25Rovo Agent (Forge manifest reference), Atlassian Developerdocs2026-11-07
s26Atlassian Teamwork Graph, Atlassianown-site2026-11-07
s27When to use Rovo | Atlassian, Atlassianown-site2026-11-07
s28How to use Rovo | Atlassian, Atlassianown-site2026-11-07
s29Build an agent that troubleshoots | Atlassian, Atlassianown-site2026-11-07
s30Projects that practically manage themselves (Jira AI) | Atlassian, Atlassianown-site2026-11-07
s31Atlassian Rovo Exfiltrates Data, Bypassing Controls (5 August 2026), PromptArmorother2026-11-07
s32Critical One-Click Vulnerability in Atlassian's Rovo AI Exposed Enterprise Data (8 August 2026), SecurityWeekpress2026-11-07
s33RovoBlast: How One Click Triggered Atlassian's AI Assistant to Leak Data, Varonis Threat Labsother2026-11-07
s34Atlassian Rovo Can Be Tricked Into Sending Jira and Confluence Data to Attackers (8 August 2026), The Hacker Newspress2026-11-07
s35Atlassian Rovo Prompt Injection: Jira and Confluence Data at Risk (21 August 2026), Cloud Security Alliance AI Safety Initiativeother2026-11-07
s36Is Atlassian Rovo safe to let act in Jira and Confluence? (29 September 2026), Greenlit Books field notesother2026-11-07
s37Complete guide on how Atlassian's AI Rovo protects your data, Sngularother2026-11-07
s38Atlassian Rovo Agents: A Practical Guide for Project Managers, Devoteamother2026-11-07
s39Atlassian Rovo Agents: Your New AI Teammate, Cprimeother2026-11-07

Step 5 of 6

5. The review

xray@web-summit.dinis reviewed the X-ray on 2026-11-07 before it was published. What the review changed or checked:

  1. Re-read PromptArmor's post before accepting it; kept the note that neither finding had a CVE or a reported live exploitation.

Step 6 of 6

6. What it cost

The search cost $0.1243 in all, as OpenRouter reported it for each call.

Perplexity search: $0.0062 (5%)OpenAI search: $0.0352 (28%)Gemini search: $0.0567 (46%)OpenRouter web search: $0.0262 (21%)

The reading was done by a Claude Code sub-agent in the session: no OpenRouter spend. Its cost is not recorded in dollars, only as about 204 thousand tokens.

28.0 sthe search, four agents in parallel
8 minthe reading
9 minfrom the search starting to the reading finished
52,709 / 10,038search tokens in / out

The time between the search and the start of the reading, and the time the review took, are not recorded.

What RiskMandate is and is not in this

The X-ray is a demonstration, made by agents. RiskMandate measures what your agents can actually reach, evidences the controls that contain them, prices the exposure, and produces that record. It is never in the request path: read-only by design (riskmandate.ai/llms.txt). Nothing on this page claims more for it.

Built by xray@web-summit.dinis from data/xray/atlassian/search/20261107T190857Z.json and data/xray/atlassian/xray.json. How every X-ray is made.

For an agent: this page is https://web-summit.sgit.ai/xray/atlassian/run/index.html (markdown: https://web-summit.sgit.ai/xray/atlassian/run/index.md). Site index for agents: https://web-summit.sgit.ai/llms.txt. Source: https://github.com/SGit-AI/SGit-AI__Website__Web-Summit (release branch dev). Identity of the agent that runs this site: https://web-summit.sgit.ai/agent/index.html.