magnus919_agent-skills/capacity-and-cost-engineering

Capacity and Cost Engineering

Connect demand, performance, reliability, and spend into defensible capacity and cost decisions.

Why Install This Skill

Every service that serves users has a capacity limit and a cost. When your agent can model capacity, calculate unit cost, define budget controls, and require load-test evidence for capacity claims, it stops treating infrastructure as "someone else's problem" and starts making decisions that respect real-world constraints. This skill fills the gap between the financial team's P&L models (which don't know what a request costs in compute) and the platform team's infrastructure-as-code (which doesn't know why a specific SLO target was chosen or what it costs).

After installing this skill, your agent can: project capacity from growth forecasts with utilization targets and scaling triggers; model multi-tenant demand distributions, hot tenants, partition skew, and pooled versus siloed headroom; connect tier promises to quotas, admission, and contextual fairness evidence; calculate platform baseline, tenant-variable, and allocated unit cost; define budget thresholds with operational consequences (alert, throttle, deny); design representative per-tenant load and soak tests as mandatory capacity evidence; and resolve SLO-cost tradeoffs with explicit evidence, ownership, and accountability.

What You Get

Directory	What it provides
SKILL.md	Core methodology: connected dimensions (demand/performance/reliability/spend), multi-tenant loading route, working method with five steps, four named scenarios, routing table to adjacent skills, and guardrails against generic cloud-cost tips and universal thresholds
README.md	This human-facing overview
references/discovery-brief.md	Ownership boundary analysis for financial, platform, SRE, analytics, SaaS architecture, security, software architecture, readiness, roadmap, and recovery concerns
references/multi-tenant-capacity-and-unit-cost.md	Original method for tenant distributions, hot tenants, partition skew, pooled/siloed headroom, tier promises, admission, fairness evidence, shared-cost allocation, and tenant-variable unit cost
references/source-index.md	Public provenance and transformation boundary
templates/capacity-model.md	Fillable capacity model: demand assumptions, capacity-unit mapping, utilization targets with rationale, scaling triggers, evidence sources, ownership, and tradeoffs
templates/unit-economics-record.md	Fillable unit-economics record: unit definition, cost numerator with allocation method, demand denominator, unit-cost calculation formula, cost-per-SLO comparison, and structured assumptions/evidence/ownership/tradeoffs fields
templates/load-soak-test-plan.md	Fillable load/soak test plan: objective, target throughput, duration, environment requirements, success criteria (latency percentiles, error rate, utilization), data collection, and evidence record
templates/budget-quota-decision.md	Fillable budget/quota decision: budget owner, period, thresholds (alert/soft/hard), quota/rate-limit configuration, enforcement mechanism, operational behavior at each threshold, cost attribution, and approval
templates/slo-cost-tradeoff-record.md	Fillable SLO-cost tradeoff record: SLO under discussion, current and projected cost, alternative SLO comparison, degradation path, error budget impact, accountable owner, and approval
templates/tenant-capacity-model.md	Fillable tenant capacity and unit-cost model covering profiles, skew, pooled/siloed comparison, quotas, fairness, cost allocation, and representative per-tenant load/soak evidence
evals/evals.json	Ten output-quality evaluation cases covering general capacity/cost decisions plus tenant distributions, pooled/siloed headroom, fairness, tenant-variable cost, and routing boundaries

Quick Start

No setup required. The skill is pure methodology — no scripts, no API keys, no runtime dependencies.

To use: ask your agent to model capacity for a service, calculate unit cost, define budget controls, plan a load test, or resolve an SLO-cost tradeoff. The skill loads when the task matches its trigger conditions and provides step-by-step guidance plus fillable templates for each artifact.

Triggers

Load this skill when the task involves:

• Projecting capacity from a growth forecast
• Sizing capacity for a peak event (launch, seasonal, Black Friday)
• Calculating unit cost at the infrastructure level
• Defining budget thresholds, spending alerts, or hard caps
• Designing quota or rate-limit enforcement
• Planning or reviewing a load or soak test as capacity evidence
• Resolving an SLO-cost tradeoff or cost-constrained reliability decision
• Reviewing a cost anomaly or attributing cost to services/teams
• Modeling multi-tenant demand distributions, hot tenants, partition skew, quotas, fairness, pooled/siloed headroom, or tenant-variable unit cost

Requirements

• No runtime dependencies, API keys, or system tools.
• No specific Python version, package, or service required.
• The skill references templates that any agent can fill; no special tooling is needed.