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 arbazkhan971/godmode --skill costgit clone --depth 1 https://github.com/arbazkhan971/godmodeWrote 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/arbazkhan971/godmode/cost)<a href="https://agentmods.dev/skills/arbazkhan971/godmode/cost"><img src="https://agentmods.dev/badge/skills/arbazkhan971/godmode/cost.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 216 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00028 | $0.02894 |
| Opus 5 | $0.00014 | $0.01447 |
| Sonnet 5 | $0.00006 | $0.00579 |
| Haiku 4.5 | $0.00003 | $0.00289 |
Grade A, and why
cost 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 8d 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 -s http://localhost:8080/api/costs/summary | jq .total How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cost — Cloud Cost Optimization
Activate When
- User invokes
/godmode:cost - User says "reduce cloud costs," "optimize spending," "why is our bill so high?"
- User asks about right-sizing, reserved instances, or spot pricing
- Godmode orchestrator detects infrastructure cost concerns
- After
/godmode:infraprovisions resources that need cost governance
Workflow
Step 1: Inventory Cloud Resources
Discover all provisioned resources and their current costs:
COST INVENTORY:
Provider: <AWS | GCP | Azure | Multi-cloud>
Account(s): <account IDs in scope>
Region(s): <regions in scope>
Time period: <billing period to analyze>
Resource categories:
Compute: <EC2/GCE/VMs — count, types, monthly cost>
Storage: <S3/GCS/Blob — volume, monthly cost>
Database: <RDS/CloudSQL/CosmosDB — instances, monthly cost>
Network: <data transfer, load balancers, monthly cost>
Containers: <ECS/GKE/AKS — clusters, monthly cost>
Serverless: <Lambda/Functions — invocations, monthly cost>
Other: <CDN, DNS, monitoring, etc.>
Step 2: Utilization Analysis
Measure actual usage versus provisioned capacity:
Compute Utilization
COMPUTE UTILIZATION:
| Instance | Type | Avg CPU | Avg Mem | Verdict |
|--|--|--|--|--|
| <instance-1> | m5.2xl | 12% | 25% | OVERSIZE |
| <instance-2> | t3.micro | 89% | 92% | UNDERSIZE |
| <instance-3> | c5.large | 45% | 60% | OK |
| <instance-4> | m5.xl | 3% | 8% | IDLE |
Thresholds:
IDLE: < 5% CPU and < 10% memory for 14+ days
OVERSIZE: < 30% CPU or < 40% memory sustained
UNDERSIZE: > 80% CPU or > 85% memory sustained
OK: within healthy range
Storage Utilization
STORAGE UTILIZATION:
| Bucket/Volume | Size | Access | Last Hit | Verdict |
|--|--:|--|--|--|
| <bucket-1> | 2.3 TB | Frequent | Today | OK |
| <bucket-2> | 500 GB | None | 90d ago | ARCHIVE |
| <volume-1> | 1 TB | None | Never | DELETE |
| <snapshot-old> | 200 GB | N/A | 180d ago | DELETE |
Database Utilization
DATABASE UTILIZATION:
| Instance | Type | Avg CPU | Storage | Verdict |
|--|--|--:|--:|--|
| <rds-prod> | db.r5.xl | 35% | 40% | OK |
| <rds-staging> | db.r5.xl | 5% | 10% | OVERSIZE |
| <rds-dev> | db.m5.lg | 2% | 5% | SCHEDULE |
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.
- 8d ago First seen · 302 lines · 28 tokens per session scan A f3340ca4d40f
cost is a skill published in the GitHub repository arbazkhan971/godmode (26 stars, last pushed 10d ago), licensed MIT. It adds 28 tokens to every session and 2,894 once invoked, about $0.0001 per session on Opus 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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bailian-train-deploy
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orca-config-origin
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orca-account-health
Cloud account coverage and sync-health audit — lists every connected cloud account, sync status, scanner deployment, integration health, and flags blind spots before any audit, investigation, or security review. Use when user asks about coverage, account health, sync status, scanner deployment, "are we monitoring X"…