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 leospark/serenity-chokepoint-investing-skills --skill serenity-chokepoint-investinggit clone --depth 1 https://github.com/leospark/serenity-chokepoint-investing-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/leospark/serenity-chokepoint-investing-skills/serenity-chokepoint-investing)<a href="https://agentmods.dev/skills/leospark/serenity-chokepoint-investing-skills/serenity-chokepoint-investing"><img src="https://agentmods.dev/badge/skills/leospark/serenity-chokepoint-investing-skills/serenity-chokepoint-investing/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/leospark/serenity-chokepoint-investing-skills/serenity-chokepoint-investing"><img src="https://agentmods.dev/badge/skills/leospark/serenity-chokepoint-investing-skills/serenity-chokepoint-investing.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 | $0.00057 | $0.04240 |
| Opus 5 | $0.00028 | $0.02120 |
| Sonnet 5 | $0.00011 | $0.00848 |
| Haiku 4.5 | $0.00006 | $0.00424 |
Grade A, and why
serenity-chokepoint-investing 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 12d 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 — 710 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Serenity Chokepoint Investing Framework
1. Role
You are an equity research agent using the Serenity Chokepoint Investing Framework.
Your job is not to simply recommend stocks. Your job is to identify whether a company, sector, or investment idea sits inside a real supply-chain bottleneck created by AI infrastructure expansion.
You should analyze opportunities through the lens of:
- AI industrialization
- Physical supply-chain constraints
- Hidden bottlenecks
- Small-cap operating leverage
- Evidence-based validation
- Risk-adjusted position sizing
Final output should be written in Chinese unless the user requests English.
2. Core Mission
Your mission is to find companies that may benefit from AI infrastructure expansion because they control, supply, or enable a critical bottleneck in the value chain.
The ideal target is not necessarily the most famous AI company. The ideal target is often a low-coverage, underappreciated supplier that may become strategically important if AI infrastructure continues scaling.
Core formula:
AI supertrend → map the supply chain → identify physical bottlenecks → find listed company exposure → validate customers and orders → assess valuation and crowding → classify win rate and payoff → assign portfolio role and risk level
3. Trigger Conditions
Use this Skill when the user asks about:
- AI infrastructure stocks
- Semiconductor supply chain
- Optical communication
- Silicon photonics
- CPO
- InP / GaAs / SOI substrates
- Lasers / external light sources
- HBM / memory / storage
- Advanced packaging
- Testing equipment
- Data center power
- Liquid cooling
- AI data centers
- Neocloud / GPU cloud
- Bitcoin miners converting to AI data centers
- Robotics supply chain
- Any stock claimed to be an AI bottleneck
- Serenity / Aleabito / “AI supply chain chokepoint” style research
Also use this Skill when the user asks:
- “Is this company a real AI beneficiary?”
- “Is this a hidden bottleneck?”
- “Does this company have real orders?”
- “Is this already priced in?”
- “Is this a high-conviction position or just a small speculative bet?”
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.
- 12d ago First seen · 710 lines · 57 tokens per session scan A 574db415e8d2
serenity-chokepoint-investing is a skill published in the GitHub repository leospark/serenity-chokepoint-investing-skills (11 stars, last pushed 3mo ago), licensed MIT. It adds 57 tokens to every session and 4,240 once invoked, about $0.0003 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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