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 alivirgo/Major-AI-Skills --skill llm-cost-latency-benchmarkgit clone --depth 1 https://github.com/alivirgo/Major-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/skills/alivirgo/major-ai-skills/llm-cost-latency-benchmark)<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/llm-cost-latency-benchmark"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/llm-cost-latency-benchmark/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/alivirgo/major-ai-skills/llm-cost-latency-benchmark"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/llm-cost-latency-benchmark.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 | $0.00030 | $0.00317 |
| Opus 5 | $0.00015 | $0.00159 |
| Sonnet 5 | $0.00006 | $0.00063 |
| Haiku 4.5 | $0.00003 | $0.00032 |
Grade A, and why
llm-cost-latency-benchmark 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 today.
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
Cost and Latency Benchmark
Scope
Define the request population, concurrency, warm-up policy, cache state, budget, and required quality floor. Read current provider pricing from an authoritative source and record its date; do not hard-code remembered prices as current.
Procedure
Measure wall-clock latency around the complete workflow, including retrieval, tools, retries, and queueing. Separate time to first output from time to completion when streaming. Use provider-reported usage where available.
Checks
Track input, cached input, output, and other separately billed usage using the provider's documented units. Include failed and retried requests in totals. Mark unavailable usage as unknown instead of estimating it silently.
Failure Handling
Report counts and latency percentiles with the measurement method and sample size. Separate cold and warm runs. Compare only configurations that meet the agreed quality floor and do not extrapolate small synthetic tests as production guarantees.
Deliverable
Deliver raw sanitized measurements, pricing references, cost arithmetic, and configuration. A faster response that fails acceptance checks is not an optimization win.
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.
- today First seen · 35 lines · 30 tokens per session scan A bef50ab516f1
llm-cost-latency-benchmark is a skill published in the GitHub repository alivirgo/Major-AI-Skills (1 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 317 once invoked, about $0.0002 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 2026-09-12.
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