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 fatihguner/foreman --skill black-swansgit clone --depth 1 https://github.com/fatihguner/foremanWrote 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/fatihguner/foreman/black-swans)<a href="https://agentmods.dev/skills/fatihguner/foreman/black-swans"><img src="https://agentmods.dev/badge/skills/fatihguner/foreman/black-swans/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/fatihguner/foreman/black-swans"><img src="https://agentmods.dev/badge/skills/fatihguner/foreman/black-swans.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00094 | $0.02710 |
| Opus 5 | $0.00047 | $0.01355 |
| Sonnet 5 | $0.00019 | $0.00542 |
| Haiku 4.5 | $0.00009 | $0.00271 |
Grade A, and why
black-swans 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 4d 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 — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Read runtime and advisory rules before applying this skill. Other Foreman layers and the catalog are in ../../content/, relative to this SKILL.md.
Black Swan Theory
On September 15, 2008, Lehman Brothers filed for the largest bankruptcy in American history. Within weeks, the global financial system stood at the brink of collapse. Virtually no mainstream economist had predicted the crisis. The models were elegant, the data was abundant, and the conclusions were catastrophically wrong. Nassim Nicholas Taleb had a name for this kind of event -- a Black Swan -- and his 2007 book of the same title had warned, with uncomfortable precision, that the financial system was a powder keg. The concept has since become indispensable vocabulary for anyone who takes risk seriously.
A Black Swan is an event that satisfies three criteria: it is an outlier beyond the realm of regular expectations, it carries extreme impact, and human nature compels us to fabricate explanations for it after the fact, making it seem predictable in retrospect. The theory does not concern itself with predicting these events -- that is the point. It concerns itself with acknowledging their inevitability and structuring decisions accordingly.
The Framework
Taleb's argument rests on a distinction between two domains of uncertainty, which he labels Mediocristan and Extremistan.
Mediocristan vs. Extremistan
| Domain | Characteristics | Examples |
|---|---|---|
| Mediocristan | Outcomes cluster around the mean; no single observation can dramatically alter the aggregate | Human height, calorie consumption, car accident rates |
| Extremistan | A single observation can disproportionately dominate the total; winner-take-all dynamics prevail | Book sales, wealth distribution, startup valuations, pandemic deaths |
Most business decisions operate in Extremistan, yet most business tools assume Mediocristan. This mismatch is the source of strategic catastrophe.
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.
- 4d ago Changed · +175 lines · +94 tokens per session 3218862af1d5
- 10d ago First seen · 1 lines · 0 tokens per session scan A 3d82118dc79a
black-swans is a skill published in the GitHub repository fatihguner/foreman (50 stars, last pushed 5d ago), licensed MIT. It adds 94 tokens to every session and 2,710 once invoked, about $0.0005 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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