Protects and restores data — backup coverage and scope, retention, immutability against ransomware, and proving restores actually work. Use this to design a backup regime, verify restores, plan retention, protect backups from ransomware, or recover from data loss.
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Nobody wants backups; they want restores. The distinction is not pedantic — organizations discover the difference during the only event that matters.
Recovery objectives and which processes must survive are set by
operations:business-continuity-and-resilience. This skill delivers against them.
Most backup gaps are things nobody thought to include: a database somebody stood up outside the standard process, configuration that only exists in a running system, data in a SaaS platform assumed to be the vendor's responsibility, or a developer's machine holding the only copy of something.
Reconcile backup coverage against the asset register from
it-operations:it-asset-management on a cadence and treat the difference as a finding. An untested
assumption of coverage is the normal state of affairs.
Note that SaaS providers protect against their failures, not against your deletion or a malicious insider. Read what the contract actually commits to, rather than what the marketing implies.
Three copies, two media or platforms, one off-site — and, since ransomware, one immutable or offline.
Modern ransomware deliberately targets backups first, using the credentials it found on the way in. A backup system reachable with production credentials will be encrypted alongside production. Immutable storage or genuinely offline copies are what survive this, and it is the difference between an outage and an extinction event.
Retention has to satisfy operational recovery, legal and regulatory obligations, and data protection
requirements — which pull in opposite directions. Data protection law obliges deletion of personal
data you no longer have a basis to keep, and indefinite backup retention conflicts with that
directly. Settle it with legal-risk:privacy-and-data-protection.
Know how you would satisfy a deletion request that touches backups, before one arrives.
A backup job reporting success proves a file was written. It says nothing about whether the data is complete, uncorrupted, or restorable in a usable time.
Test on a schedule, restore to a separate environment, and verify the application actually works on the restored data rather than that the bytes arrived. Record how long it took — that measurement is the only honest input to an RTO, and it is invariably longer than assumed.
Test the full-scale case at least annually. Restoring one file proves the mechanism; restoring the system proves the plan.
references/sources.md in this skill lists the outside authorities that settle the questions
here — what each one is authoritative for, and what you may do with it. Check them before
answering on anything they cover, and cite what you used. Most are free to read and not free
to reproduce; the use note on each is binding.
Backup platforms: Veeam, Rubrik, Cohesity, Commvault, Acronis, and similar.
SaaS data is the gap people miss. Microsoft 365, Google Workspace, and Salesforce retain for a short window and no longer; Veeam, Druva, AvePoint, Keepit, and similar cover it.
The tool is not the control. An untested restore is not a backup, whatever the console reports.
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Designs and audits who can reach what — authentication, authorization models, privileged access, service credentials, and joiner-mover-leaver process. Use this to design a permissions model, run an access review, reduce standing privilege, handle offboarding, set up SSO or MFA, manage service and machine credentials, or diagnose why permissions have sprawled.
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Concentrates marketing and sales effort on a named set of accounts rather than on volume — qualifying whether the model fits your economics at all, building the account list and the buying group inside each, tiering effort against account value, coordinating so the account experiences one campaign rather than several, and measuring account progression instead of leads. Use this to decide whether to run an account-based program, build one, or work out why an existing one produces activity and no pipeline.
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Gets new users from signup to first real value — signup flow, onboarding, time-to-value, and the early experience that determines whether someone becomes a user or a lapsed account. Use this to design or fix signup and onboarding, diagnose why signups do not convert to active use, reduce time-to-value, or decide what a new user must accomplish first.
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Designs orchestrator-and-subagent hierarchies for a repository — splitting agents by exclusive write surface, pairing every producer with an independent auditor, and enforcing the split with a script that runs in CI. Use this whenever the user wants to set up, expand, audit, or fix a multi-agent or subagent structure for a codebase; asks how to divide work between agents; wants agent charters, roles, or a surface map written; or is hitting agents that collide on the same files, review their own work, or drift from their remit. Also use when sizing a roster or deciding whether a new agent is justified.
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Governs models and AI systems in production — intended use, evaluation, monitoring, human oversight, documentation, and the decision to deploy or retire. Use this before deploying a model or AI feature, when defining evaluation criteria, when a model's behavior has drifted, when assessing AI risk or regulatory exposure, or when deciding whether an AI system is fit for a consequential decision.
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Produces executive-level research — market sizing, competitor mapping, trend analysis, and strategic intelligence — grounded in cited sources with the confidence in each claim made explicit. Use this to analyze a market or industry, map competitors, evaluate a market-entry or build-versus-buy decision, produce a research brief, or assemble evidence for a decision. Also use when comparing options that need a structured, evidence-based verdict rather than an opinion.
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