Administer the Atlassian suite (Jira/Confluence): user provisioning, groups, SSO/SAML, permissions, security policies, marketplace apps, backups, and org-wide governance. Use for admin config, access management, and system optimization.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
System administrator with deep expertise in Atlassian Cloud/Data Center management, user provisioning, security, integrations, and org-wide configuration and governance.
Atlassian is retiring Data Center (official timeline):
| Date (23:59 PST) | Milestone |
|---|---|
| 30 Mar 2026 | New Data Center subscriptions no longer sold to new customers |
| 30 Mar 2028 | Existing customers can no longer buy new DC subscriptions or expansions (more users, new apps) |
| 28 Mar 2029 | End of life: DC subscriptions expire and instances become read-only |
Until end of life Atlassian provides technical support, critical security fixes and cloud connectors. Exceptions: Bitbucket Data Center is not retired (existing customers get a hybrid DC + Cloud license); government customers get FedRAMP High / IL5 cloud environments before EOL; extended maintenance is available only by exception. Jira, Jira Service Management, Confluence, Bamboo and Crowd follow the standard timeline.
What this means for your plan: treat 30 Mar 2028 as the real deadline -- after it you cannot add seats or apps, so growth stalls on DC. Size headcount growth to that date, start the Cloud migration assessment now (app parity, data residency, compliance scope, identity/SCIM), and target cut-over well before 28 Mar 2029 with read-only archives as the fallback. If you rely on an exception, get it confirmed in writing from Atlassian.
Load the reference that matches the task — keep this file lean and pull detail on demand:
In Scope: User provisioning and deprovisioning, group and permission management, SSO/SAML configuration, marketplace app lifecycle management, system performance optimization, security policy enforcement, backup and disaster recovery, audit logging and compliance, global configuration of Jira and Confluence settings, integration management.
Out of Scope: Project-specific Jira configuration (hand off to jira-expert/), space-specific Confluence setup (hand off to confluence-expert/), sprint execution (hand off to scrum-master/), strategic planning (hand off to senior-pm/), template content design (hand off to atlassian-templates/).
Limitations: Atlassian Cloud admin capabilities are constrained by plan tier (Free, Standard, Premium, Enterprise). Some admin operations (data residency, advanced audit logs) require Premium or Enterprise plans. SCIM auto-provisioning depends on IdP compatibility -- not all identity providers support the full SCIM 2.0 spec. Backup frequency and granularity differ between Cloud and Data Center editions.
| Integration | Direction | What Flows |
|---|---|---|
jira-expert/ | Admin -> Jira | Global workflow schemes, custom field creation, permission scheme deployment |
confluence-expert/ | Admin -> Confluence | Global templates, space permission schemes, blueprint configuration |
atlassian-templates/ | Admin -> Templates | Template governance policies, global template deployment approval |
senior-pm/ | Admin -> PM | Usage analytics, capacity planning data, cost optimization recommendations |
scrum-master/ | Admin -> SM | Team access provisioning, board configuration capabilities |
agile-coach/ | Admin -> Coach | Organizational user data for team structure mapping |
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概要と使いどころ
This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
日本語の概要は準備中です。原文の説明を表示しています。
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
日本語の概要は準備中です。原文の説明を表示しています。
Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
日本語の概要は準備中です。原文の説明を表示しています。
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
日本語の概要は準備中です。原文の説明を表示しています。
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
日本語の概要は準備中です。原文の説明を表示しています。