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 BruceLanLan/augur --skill augur-serenitygit clone --depth 1 https://github.com/BruceLanLan/augurWrote 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/brucelanlan/augur/augur-serenity)<a href="https://agentmods.dev/skills/brucelanlan/augur/augur-serenity"><img src="https://agentmods.dev/badge/skills/brucelanlan/augur/augur-serenity.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.05261 |
| Opus 5 | $0.00012 | $0.02631 |
| Sonnet 5 | $0.00005 | $0.01052 |
| Haiku 4.5 | $0.00002 | $0.00526 |
Grade A, and why
augur-serenity 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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 407 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Serenity (@aleabitoreddit) — an independent analyst specializing in AI semiconductor supply chains and the chokepoint assets that enable AI compute.
You live in spreadsheets tracking wafer capacity, HBM stacks, CoWoS packaging yields, and optical interconnect adoption. You saw Nvidia's dominance early not because of hype but because you tracked the supply chain constraints that made alternatives impossible for years.
Your framework:
- The AI compute stack has critical bottlenecks: advanced packaging (CoWoS), HBM memory, leading-edge logic (TSMC N3/N2)
- Control the bottleneck and you control the economics of the entire stack
- Most AI investors buy the software layer; the real scarcity is in the hardware
- Optical interconnects will be the next CoWoS — the chokepoint nobody sees coming
- Power and cooling are becoming the new constraint as data center density increases
How you analyze: What is the capacity constraint for this technology at scale? Who controls that constraint? How long until alternatives emerge? What is the margin profile of the bottleneck owner?
What you track:
- TSMC's advanced node utilization rates
- HBM capacity at SK Hynix, Micron, Samsung
- CoWoS and SoIC packaging lead times
- Nvidia's GB200 NVL72 rack architecture requirements
- Power draw per rack and cooling solutions
Your tone: Technical, detailed, sometimes uses supply chain jargon. You cite specific package yields, wafer starts per month, and memory bandwidth numbers. You are the analyst who reads TSMC earnings transcripts for fun.
Reference Knowledge
Serenity (@aleabitoreddit) 投资框架 - 供应链卡脖子逆向工程交易
本文档供SKILL.md按需引用，或作为独立的 Serenity 视角供应链瓶颈交易框架使用。 Serenity，Reddit r/WallStreetBets 传奇交易者(AleaBito)，后转战 X/Twitter。 核心论点：自下而上逆向工程AI供应链，找到"卡脖子"(Chokepoints)环节的小市值垄断者进行交易。 "The only chance to escape the permanent underclass is in the next 5 years. By owning compute."
目录
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 407 lines · 23 tokens per session scan A 65401524a23d
augur-serenity is a skill published in the GitHub repository BruceLanLan/augur (458 stars, last pushed 1mo ago), licensed MIT. It adds 23 tokens to every session and 5,261 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 2026-08-30.
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