skills/magnus919_agent-skills

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a471888676 feat(capacity-and-cost-engineering): add capacity-and-cost-engineering skill (#199 ) (#224 )

Add a new skill connecting demand, performance, reliability, and spend
decisions. Covers capacity models, unit economics, budget/quota controls,
load/soak test evidence, and SLO-cost tradeoffs with structured templates.

Includes:
- SKILL.md with connected-dimensions framework, working method, four
  labeled scenarios (growth, peak, degraded, cost-constrained), and
  routing table to six adjacent skills
- README.md with five required human-facing sections
- references/discovery-brief.md comparing ownership boundaries across
  financial-modeling, platform-engineering, SRE, product-analytics,
  production-readiness, product-roadmapping, and resilience-and-recovery
- Five fillable templates: capacity-model, unit-economics-record,
  budget-quota-decision, load-soak-test-plan, slo-cost-tradeoff-record
- evals/evals.json with five output-quality cases: growth-forecast,
  peak-event, slo-cost-conflict, quota-decision, misleading-unit-cost
- Regenerated marketplace, Codex, and llms.txt catalogs (117 skills)
- Updated root README catalog section and skill-triggers index

Co-authored-by: username <username>
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>

2026-08-02 18:41:03 -04:00

3.9 KiB

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Capacity Model

Fill this template to produce a capacity model connecting demand to infrastructure requirements over a projection horizon.

Demand assumptions

Current demand: [fill: e.g., 500 requests/second, 10,000 concurrent users, 2 TB/day ingested]
Demand unit: [fill: requests/sec, concurrent users, GB ingested, messages/sec — be specific]
Growth rate: [fill: e.g., 15% month-over-month, or flat with seasonal spike]
Known peak events: [fill: product launch, Black Friday, seasonal — date/range, expected multiplier over baseline]
Projection horizon: [fill: e.g., 6 months, 12 months]
Confidence in demand forecast: [fill: high/medium/low with rationale — what is this based on? historical data, product roadmap, market estimate?]

Capacity-unit mapping

Demand unit	Capacity unit	Mapping ratio	Rationale
[fill: e.g., 1 request/sec]	[fill: e.g., 0.25 vCPU, 256 MB memory]	[fill: e.g., measured at 70% utilization]	[fill: from load test 2026-01-15]
[fill: ...]	[fill: ...]	[fill: ...]	[fill: ...]

Utilization targets

Resource	Target utilization	Rationale	Evidence
CPU	[fill: e.g., 70%]	[fill: e.g., spiky traffic needs headroom for P99 latency]	[fill: load test at 80% showed P99 degradation]
Memory	[fill: e.g., 80%]	[fill: e.g., GC overhead acceptable up to 80%]	[fill: soak test 24h at 85% — no OOM, stable]
Storage	[fill: e.g., 75%]	[fill: e.g., provisioned IOPS degrade above 80%]	[fill: vendor docs + observed IOPS curve]
Network	[fill: e.g., 60%]	[fill: e.g., burst capacity for peak events]	[fill: ...]

Scaling triggers

Resource	Trigger threshold	Action	Lead time
[fill: CPU]	[fill: sustained > 60% for 5 min]	[fill: scale out by 2 instances]	[fill: 3 min]
[fill: Storage]	[fill: projected to hit 75% in 30 days]	[fill: provision additional 500 GB]	[fill: 7 days for procurement]

Capacity projection

Period	Projected demand	Required capacity	Scaling action	Estimated cost
[fill: Month 1]	[fill: ...]	[fill: ...]	[fill: none]	[fill: $X]
[fill: Month 2]	[fill: ...]	[fill: ...]	[fill: scale out 2 instances]	[fill: $Y]
[fill: ...]	[fill: ...]	[fill: ...]	[fill: ...]	[fill: ...]

Assumptions

[fill: assumption about demand pattern, growth stability, peak shape]
[fill: assumption about unit cost stability, no price changes]
[fill: assumption about no architecture changes that alter capacity/demand ratio]
[fill: any other unverified assumption]

Every assumption without evidence must be labeled as such.

Evidence sources

Source	What it provides	Boundary exercised
[fill: load test 2026-01-15]	[fill: capacity/demand ratio at 70% CPU]	[fill: end-to-end]
[fill: production metrics Jan-Mar 2026]	[fill: observed growth rate]	[fill: production]
[fill: ...]	[fill: ...]	[fill: component / integration / end-to-end / production]

Ownership

Model owner: [fill: name or team]
Capacity provisioning owner: [fill: name or team — may differ from model owner]
Review cadence: [fill: e.g., monthly, or on demand change >20%]

Tradeoffs

[fill: e.g., lower utilization target → higher cost but lower latency risk]
[fill: e.g., faster scaling trigger → more responsive but more frequent provisioning events]
[fill: any tradeoff between cost, performance, reliability, or operational complexity]

3.9 KiB Raw Blame History