Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/dapi/claude-code-marketplace/cluster-efficiencygit clone --depth 1 https://github.com/dapi/claude-code-marketplaceWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.02657 |
| Opus 5 | $0.00000 | $0.01328 |
| Sonnet 5 | $0.00000 | $0.00531 |
| Haiku 4.5 | $0.00000 | $0.00266 |
Grade A, and why
cluster-efficiency scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
kubectl --context=$CONTEXT exec -n monitoring $PROM_POD -c prometheus -- wget -qO- 'http://localhost:9090/api/v1/query?query=sum+by+(namespace,pod)(increase(container_oom_events_total[7d]))' How it starts
The opening of the file, as written. The whole thing — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/cluster-efficiency — Анализ эффективности ресурсов кластера
Выполни комплексный анализ эффективности использования ресурсов кластера Kubernetes.
Аргументы
Передаются через $ARGUMENTS:
--context=NAME— Kubernetes контекст--namespace=NS— Фильтр по namespace--focus=AREA— Фокус: all, nodes, workloads, karpenter, cost--save— Сохранить отчет--compare— Сравнить с предыдущим--prometheus— Использовать Prometheus--deep— Глубокий анализ с подагентами
Режим работы
Фаза 0: Сбор контекста (ОБЯЗАТЕЛЬНО!)
Определи контекст Kubernetes:
CONTEXT="${CLUSTER_EFFICIENCY_CONTEXT:-$(kubectl config current-context)}"
echo "Using context: $CONTEXT"
ПЕРЕД любым анализом:
- Прочитай журнал изменений ресурсов:
cat docs/resource-changes.md 2>/dev/null || echo "Журнал не найден"
- Получи OOM историю:
kubectl --context=$CONTEXT get events -A --field-selector reason=OOMKilling --sort-by='.lastTimestamp' | tail -20
kubectl --context=$CONTEXT get pods -A -o json | jq -r '.items[] | select(.status.containerStatuses[]?.lastState.terminated.reason == "OOMKilled") | "\(.metadata.namespace)/\(.metadata.name)"' 2>/dev/null
- Сформируй "защитный список" workloads, для которых снижение ЗАПРЕЩЕНО:
- Упомянутые в откатах resource-changes.md
- Имевшие OOM за последние 7 дней
- Production namespace (без явной просьбы)
Фаза 1: Базовый анализ
SCRIPT_DIR=$(find ~/.claude -path "*/cluster-efficiency/scripts/cluster-efficiency.sh" -type f 2>/dev/null | head -1 | xargs dirname)
cd "$SCRIPT_DIR" && ./cluster-efficiency.sh $ARGUMENTS
Фаза 2: Глубокий анализ (--deep)
Если передан --deep или базовый анализ выявил серьёзные проблемы — запусти параллельно через Task tool три подагента (subagent_type="general-purpose"). Передай каждому контекст и защитный список.
Промпт для node-analyzer:
Ты — специализированный агент для анализа эффективности нод Kubernetes.
Контекст: $CONTEXT (используй во всех kubectl командах: --context=$CONTEXT)
Задачи:
1. Собрать метрики нод:
kubectl --context=$CONTEXT get nodes -o wide
kubectl --context=$CONTEXT top nodes
kubectl --context=$CONTEXT get nodes -L karpenter.sh/nodepool -L karpenter.sh/capacity-type
kubectl --context=$CONTEXT describe nodes | grep -E "^Name:|Allocatable:|Allocated resources:|cpu|memory"
2. Классифицировать ноды по типу (system/worker/spot/on-demand), управлению (static/Karpenter) и утилизации (low <30% / normal / high >70%)
3. Выявить проблемы: ноды <30% утилизации, переоцененные workloads (высокие requests при низком usage), несбалансированное распределение
Формат вывода:
NODE EFFICIENCY ANALYSIS
========================
Context: $CONTEXT
Summary: total/system/on-demand/spot ноды
Utilization Distribution: low/normal/high
Issues Found: конкретные ноды с цифрами
Recommendations: приоритизированные действия
Отвечай на русском. Конкретные числа и имена нод.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 253 lines · 0 tokens per session scan A 677a64140f3b
cluster-efficiency is a command published in the GitHub repository dapi/claude-code-marketplace (16 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,657 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.