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 skills add sawrus/agent-guides --skill cost-optimizationgit clone --depth 1 https://github.com/sawrus/agent-guidesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sawrus/agent-guides/cost-optimization)<a href="https://agentmods.dev/skills/sawrus/agent-guides/cost-optimization"><img src="https://agentmods.dev/badge/skills/sawrus/agent-guides/cost-optimization/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sawrus/agent-guides/cost-optimization"><img src="https://agentmods.dev/badge/skills/sawrus/agent-guides/cost-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00025 | $0.01438 |
| Opus 5.5 | $0.00010 | $0.00575 |
| Sonnet 5.5 | $0.00005 | $0.00288 |
| Haiku 4.5 | $0.00003 | $0.00144 |
Grade A, and why
cost-optimization scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl http://localhost:9003/allocation \ How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Cost Optimization
Expertise: Cloud cost analysis, right-sizing recommendations, reserved/spot instances, tagging strategy, cost alerting.
When to load
When investigating unexpectedly high cloud bills, right-sizing instances, or setting up cost attribution by team/environment.
Mandatory Cost Tags (every resource)
locals {
cost_tags = {
Project = var.project # e.g. "checkout"
Environment = var.environment # prod / staging / dev
Team = var.team # e.g. "backend-team"
CostCenter = var.cost_center # e.g. "eng-platform"
ManagedBy = "terraform"
}
}
# Apply to every resource via merge(local.cost_tags, {...})
AWS Cost Discovery
# Top 10 most expensive services this month
aws ce get-cost-and-usage \
--time-period Start=$(date +%Y-%m-01),End=$(date +%Y-%m-%d) \
--granularity MONTHLY \
--metrics BlendedCost \
--group-by Type=DIMENSION,Key=SERVICE \
--query 'ResultsByTime[0].Groups | sort_by(@, &Metrics.BlendedCost.Amount) | reverse(@) | [:10]' \
--output table
# Cost by tag (Team)
aws ce get-cost-and-usage \
--time-period Start=$(date +%Y-%m-01),End=$(date +%Y-%m-%d) \
--granularity MONTHLY \
--metrics BlendedCost \
--group-by Type=TAG,Key=Team
# Idle EC2 instances (< 5% CPU, last 2 weeks)
aws cloudwatch get-metric-statistics \
--namespace AWS/EC2 \
--metric-name CPUUtilization \
--dimensions Name=InstanceId,Value=<instance-id> \
--start-time $(date -d '-14 days' --iso-8601) \
--end-time $(date --iso-8601) \
--period 1209600 --statistics Average
Right-Sizing Workflow
# Step 1: Get actual utilisation (Prometheus, last 7 days)
# CPU: avg and p99
avg(avg_over_time(instance:node_cpu_utilisation:rate5m[7d])) by (instance)
quantile_over_time(0.99, instance:node_cpu_utilisation:rate5m[7d])
# Memory: peak working set
max_over_time(node_memory_MemUsed_bytes[7d]) / node_memory_MemTotal_bytes
# Step 2: Recommendation formula
# New CPU = p99_cpu × 1.3 (30% headroom)
# New memory = peak_mem × 1.2 (20% headroom)
# Step 3: Find next smaller instance type
# AWS: use ec2-instance-selector
ec2-instance-selector --vcpus-min 2 --vcpus-max 4 \
--memory-min 4 --memory-max 8 \
--region eu-west-1 \
--output table-wide
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.
- 1mo ago First seen · 178 lines · 25 tokens per session scan A 0c98a15b22ac
cost-optimization is a skill published in the GitHub repository sawrus/agent-guides (19 stars, last pushed yesterday), licensed MIT. It adds 25 tokens to every session and 1,438 once invoked, about $0.0001 per session on Opus 5.5. 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.
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