systems-administration
Runs servers and corporate systems — patching, configuration baselines, change control, capacity, and the routine that prevents incidents. Use this to establish a patching cadence, standardize server configuration, plan a maintenance window, decide change control for infrastructure, or clean up systems that have drifted from any known state.
git clone --depth 1 https://github.com/cbrock84/headcount /tmp/systems-administration && cp -r /tmp/systems-administration/plugins/it-operations/skills/systems-administration ~/.claude/skills/systems-administrationSKILL.md
# Systems administration Well-run systems are boring. The work is in the routine that keeps them that way, and almost every serious incident traces back to a routine that was skipped. Cloud environment design belongs to `technology:cloud-infrastructure`; this is operating the systems the company runs on. ## Configuration baselines and drift Every system class needs a defined baseline: build, hardening, agents, logging, accounts. Systems built by hand from memory diverge immediately and cannot be reasoned about as a group. Drift is the real enemy. Detect it continuously and correct rather than document — a system that no longer matches its baseline is a system whose behavior under patching or failover is unknown. The strongest form is disposability: rebuild rather than repair. A system you can rebuild in an hour never accumulates the sediment of a decade of manual fixes. ## Patching as a cadence Set a regular, predictable window and hold it. Ad hoc patching means patching happens when someone worries, which is never in proportion to actual risk. Tier by exposure: internet-facing systems on the shortest cycle, then internal, then isolated. Emergency patching is a separate path with its own authority, used for actively exploited vulnerabilities — `security:vulnerability-management` decides what is urgent, this skill executes it. Track **coverage**, not activity. "Patching is running" is not an answer; "97% of servers are within 30 days, here are the twelve that are not and why" is. ## Change control proportionate to risk Heavyweight approval for trivial changes produces circumvention, and circumvention produces unrecorded changes, which is worse than no process. Tier it: standard pre-approved changes, normal changes with review, emergency changes with after-the-fact record. Every change needs an owner, a back-out plan, and a record — the back-out plan being the part most often assumed rather than written. Maintenance windows exist to make disruption predictable. Announce them, keep them, and finish inside them. ## Know what you have An unmanaged system is a system nobody patches. Reconcile what is running against `it-operations:it-asset-management` regularly, and treat anything unaccounted for as urgent — the server nobody owns is the one still running an unsupported operating system. ## Never - Repair a drifted system without correcting the baseline that let it drift. - Patch on worry rather than cadence. - Make a change with no back-out plan. - Leave a discovered unmanaged system unclaimed.
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.
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.
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.
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.
Optimizes for AI assistants and AI-generated answers — being retrievable, being cited, and being represented accurately when a model answers on your behalf. Use this when traffic is shifting from links to AI answers, when a brand is misrepresented or absent in AI responses, when planning content for retrieval rather than ranking, or when deciding how AI search changes an existing SEO program.
Improves visibility and conversion in the App Store and Google Play — metadata, keywords, screenshots, ratings, and the listing experience that turns an impression into an install. Use this to audit or optimize an app listing, plan a launch listing, diagnose poor install conversion, or improve store search visibility.
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.
Runs the planning cycle — annual budget, rolling forecast, consolidation of business unit inputs, and the variance analysis that explains actuals against plan. Use this to build or challenge a budget, run a forecast cycle, consolidate departmental submissions, explain why results diverged from plan, or improve forecast accuracy.