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augur-serenity

augur-serenity is a skill for Claude Code, Codex from BruceLanLan/augur. It costs 23 tokens per session (5,265 once invoked), scanned A, original, MIT.

An AI investment-analysis persona focused on the hardware supply chain behind artificial intelligence. It studies scarce parts and production steps such as advanced chip packaging, high-bandwidth memory, leading-edge chips, optical connections, power, and cooling.

In plain words
What is it for?
It is for analysing supply bottlenecks, who controls them, how long they may last, and which companies could benefit from owning those constraints.
Why use it?
It directs attention to physical production limits that can constrain AI growth, rather than looking only at AI software companies.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: model in frontmatter; positional $N argument; built for openclaw.

not rated 681repo +30 changed 7d ago A scan SkillSpector: pass 23 tokens original MIT

Good fit It is for analysing supply bottlenecks, who controls them, how long they may last, and which companies could benefit from owning those constraints.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/brucelanlan/augur/augur-serenity
View source ↗ BruceLanLan/augur
Install

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.

Any agent
npx skills add BruceLanLan/augur --skill augur-serenity
Clone the repo
git clone --depth 1 https://github.com/BruceLanLan/augur

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for augur-serenity

README.md
[![agentmods](https://agentmods.dev/badge/skills/brucelanlan/augur/augur-serenity/github.svg)](https://agentmods.dev/skills/brucelanlan/augur/augur-serenity)
Your own site
<a href="https://agentmods.dev/skills/brucelanlan/augur/augur-serenity"><img src="https://agentmods.dev/badge/skills/brucelanlan/augur/augur-serenity/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.

agentmods 80×15 button for augur-serenity

Your own site · 80×15
<a href="https://agentmods.dev/skills/brucelanlan/augur/augur-serenity"><img src="https://agentmods.dev/badge/skills/brucelanlan/augur/augur-serenity.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,265 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00023 $0.05265
Opus 5.5 $0.00009 $0.02106
Sonnet 5.5 $0.00005 $0.01053
Haiku 4.5 $0.00002 $0.00526

Measured 7d ago against content hash 976d670110f3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 7d 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.

src/skills/augur-serenity/SKILL.md · 407 lines

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

  1. 身份与背景
  2. 投资哲学 - Chokepoint Theory
  3. 决策框架
  4. 核心标的与案例
  5. 行为规范
  6. 口头禅与风格
  7. 评分体系

Read the full file on GitHub · 407 lines

Files

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.

Changes

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.

  1. 7d ago Changed 976d670110f3
  2. 1mo ago Changed 04d5daf4a0fd
  3. 1mo ago Changed e2fcfc58eab1
  4. 2mo ago First seen · 407 lines · 23 tokens per session scan A 65401524a23d

Subscribe to this mod's changes

augur-serenity is a skill published in the GitHub repository BruceLanLan/augur (681 stars, last pushed 8d ago), licensed MIT. It adds 23 tokens to every session and 5,265 once invoked, about $0.0001 per session on Opus 5.5. 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.

Finance and fintechHardware and IoTMulti-Agentai-agentsinvestment-analysisstock-analysisvalue-investing
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