Capacity PlanningCAUTION

1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in Anthropic's plugin directory. Plus a typed decision layer: which skill, is it safe, ship or slip. Free in-browser or npx pm-

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: capacity-planning
description: "Produce a capacity planning document for a service covering traffic forecasts, resource requirements, and scaling strategy. Use when asked to plan infrastructure capacity, forecast resource needs, model traffic growth, define scaling strategy, or produce a capacity review for a service. Produces a structured capacity plan covering current baseline metrics, growth projections, resource requirements per tier, scaling strategy, cost projections, capacity triggers, and an infrastructure action roadmap."
---

# Capacity Planning Skill

Produce a complete capacity planning document for a service. Capacity planning is not about predicting the future exactly — it is about understanding current headroom, modelling growth, and ensuring the team takes infrastructure action before a constraint becomes an incident.

A good capacity plan answers: what is running out first, how long before it runs out, what does it cost to fix it, and who decides when to act.

## Required Inputs

Ask for these if not already provided:
- **Service name and description** — what the service does and who depends on it
- **Current traffic and usage metrics** — requests per second (or per day), active users, data volume — whatever units are most natural for this service
- **Current resource utilisation** — CPU %, memory %, disk usage, connection pool utilisation, DB query throughput
- **Growth rate or projections** — historical growth rate, or known upcoming events (product launch, sales cycle, seasonal peak)
- **Tech stack and infrastructure** — cloud provider, compute type (VMs, containers, serverless), database, caching layer, CDN
- **Cost constraints** — current infrastructure spend, acceptable cost ceiling, or target cost per unit of traffic

## Output Format

---

# Capacity Plan: [Service Name]

**Service:** [Name] | **Team:** [Team name]
**Author:** [Name] | **Last updated:** [Date]
**Planning horizon:** [12 months — [Month Year] to [Month Year]]
**Review cadence:** [Quarterly]

---

## 1. Executive Summary

[3–5 sentences covering: current state, the most critical capacity constraint, the timeline before it becomes a risk, the recommended action, and the cost implication. Written for an engineering manager or VP who needs the key facts without reading the full document.]

**Critical finding:** [e.g. "The database connection pool will reach 90% utilisation within 6 weeks at current growth. Without action, this will cause request queueing and latency spikes under normal traffic."]

**Recommended immediate action:** [e.g. "Increase connection pool limit and add a read replica within the next 2 weeks."]

**Estimated cost impact:** [e.g. "Recommended changes add ~$[X]/month to infrastructure spend."]

---

## 2. Current Baseline

*All metrics are 30-day averages unless noted. Date captured: [Date]*

### Traffic

| Metric | Value | Peak (7-day) | Notes |
|---|---|---|---|
| Requests per second (avg) | [X req/s] | [X req/s] | [Peak time / day of week] |
| Requests per day | [X M/day] | [X M/day] | — |
| Active users (DAU/MAU) | [X] / [X] | — | — |
| [Service-specific metric — e.g. jobs processed/hour] | [X] | [X] | — |
| [Service-specific metric — e.g. GB ingested/day] | [X GB] | [X GB] | — |

### Compute

| Resource | Current utilisation | Instance type | Count | Notes |
|---|---|---|---|---|
| CPU (avg) | [X%] | [e.g. c5.2xlarge] | [X] | Peak: [X%] |
| Memory (avg) | [X%] | — | — | Peak: [X%] |
| Network egress | [X Mbps] | — | — | — |
| Container / pod count | [X] | [e.g. 2 vCPU / 4 GB] | — | Auto-scaling range: [X–Y] |

### Database

| Resource | Current utilisation | Spec | Notes |
|---|---|---|---|
| CPU | [X%] | [e.g. db.r5.2xlarge] | Peak: [X%] |
| Memory | [X%] | [X GB RAM] | — |
| Storage used | [X GB] of [Y GB] ([Z%]) | [X GB provisioned] | Growth: [~X GB/month] |
| IOPS (avg) | [X] of [Y provisioned] | [Y IOPS] | Peak: [X IOPS] |
| Connection pool | [X] of [Y max] ([Z%]) | Max connections: [Y] | [ORM pool size: X] |
| Query P99 latency | [X ms] | — | [Slowest query: X] |
| Read/write ratio | [X%] reads / [Y%] writes | — | — |

### Cache

| Resource | Current utilisation | Spec | Notes |
|---|---|---|---|
| Memory used | [X GB] of [Y GB] ([Z%]) | [e.g. cache.r6g.large] | Eviction rate: [X%] |
| Hit rate | [X%] | — | Miss rate: [Y%] |
| Connections | [X] | Max: [Y] | — |

### Storage / Object Store

| Resource | Current usage | Growth rate | Notes |
|---|---|---|---|
| [S3 / GCS / Blob] | [X GB / TB] | [~X GB/month] | [Lifecycle policies in place? Y/N] |
| Disk (if applicable) | [X GB] of [Y GB] | [~X GB/month] | [RAID / EBS type] |

### Cost Baseline

| Component | Current monthly cost | % of total |
|---|---|---|
| Compute (app servers) | $[X] | [X%] |
| Database | $[X] | [X%] |
| Cache | $[X] | [X%] |
| Storage | $[X] | [X%] |
| CDN / bandwidth | $[X] | [X%] |
| Other ([describe]) | $[X] | [X%] |
| **Total** | **$[X]** | 100% |

**Unit economics:** $[X] per [1,000 requests / 1,000 users / GB processed]

---

## 3. Growth Projections

### Assumptions

| Assumption | Value | Source | Confidence |
|---|---|---|---|
| Monthly traffic growth rate | [X%] | [Historical trend / product forecast] | [High / Medium / Low] |
| Seasonal peak factor | [+X% in [month(s)]] | [Last year's data / expected launch] | [High / Medium] |
| Upcoming events | [e.g. Marketing campaign — [Month], expected +[X]% traffic spike] | [Marketing plan] | [Medium] |
| User growth | [X new users/month] | [Sales pipeline / growth model] | [Medium] |
| Data growth | [X GB/month] | [Current trend] | [High] |

### Traffic Forecast

| Timeframe | Req/s (avg) | Req/s (peak) | DAU | Data volume (cumulative) |
|---|---|---|---|---|
| **Now** (baseline) | [X] | [X] | [X] | [X GB/TB] |
| **+3 months** | [X] | [X] | [X] | [X GB/TB] |
| **+6 months** | [X] | [X] | [X] | [X GB/TB] |
| **+12 months** | [X] | [X] | [X] | [X GB/TB] |

*Growth formula: [Baseline] × (1 + [monthly rate])^[months] + seasonal adjustment*

###

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (5)

templates/pm-discovery-agent/skills/assumption-mapper/SKILL.md

templates/pm-discovery-agent/skills/discovery-interview-guide/SKILL.md

templates/pm-discovery-agent/skills/job-story-mapper/SKILL.md

templates/pm-discovery-agent/skills/user-interview-synthesis/SKILL.md

templates/pm-launch-agent/skills/content-calendar/SKILL.md

Gates applied: no_behavioural_pass.