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.
git clone --depth 1 https://github.com/Amey-Thakur/AI-SKILLSWrote 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/commands/amey-thakur/ai-skills/cost-optimization-review)<a href="https://agentmods.dev/commands/amey-thakur/ai-skills/cost-optimization-review"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/cost-optimization-review/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/commands/amey-thakur/ai-skills/cost-optimization-review"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/cost-optimization-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00018 | $0.00235 |
| Opus 5 | $0.00009 | $0.00118 |
| Sonnet 5 | $0.00004 | $0.00047 |
| Haiku 4.5 | $0.00002 | $0.00023 |
Grade A, and why
cost-optimization-review scanned grade A with 0 findings 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 11d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
You were invoked as a slash command. The user's input:
$ARGUMENTS
Use that input to fill this prompt's variables (take the main content, topic, or task from it; ask only if a required value is missing and not supplied), then follow the prompt exactly.
Review this spend:
{spend}
Usage: {usage}
Use cloud-cost-optimization, media-storage-tiering, and agent-vendor-operations.
Produce:
- The largest costs and what drives each.
- Idle and over-provisioned resources, with evidence.
- Storage that should be tiered or expired.
- Vendor subscriptions with unused seats or overlap.
- Savings ranked by size, each with effort and risk.
- What must not be cut, and why.
- The realistic total.
Rules: attack the largest cost rather than the easiest. State what each cut makes riskier. Distinguish waste from capacity that exists for peak. Say where you cannot judge without utilisation data rather than assuming.
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.
- 11d ago First seen · 37 lines · 18 tokens per session scan A e4a3a0b686a1
cost-optimization-review is a command published in the GitHub repository Amey-Thakur/AI-SKILLS (7 stars, last pushed 5d ago), licensed MIT. It adds 18 tokens to every session and 235 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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