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 winstonkoh87/Athena-Public --skill bionic-decision-enginegit clone --depth 1 https://github.com/winstonkoh87/Athena-PublicWrote 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/winstonkoh87/athena-public/bionic-decision-engine)<a href="https://agentmods.dev/skills/winstonkoh87/athena-public/bionic-decision-engine"><img src="https://agentmods.dev/badge/skills/winstonkoh87/athena-public/bionic-decision-engine/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/winstonkoh87/athena-public/bionic-decision-engine"><img src="https://agentmods.dev/badge/skills/winstonkoh87/athena-public/bionic-decision-engine.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 | $0.00041 | $0.02123 |
| Opus 5.5 | $0.00016 | $0.00849 |
| Sonnet 5.5 | $0.00008 | $0.00425 |
| Haiku 4.5 | $0.00004 | $0.00212 |
Grade A, and why
bionic-decision-engine 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 1mo 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 — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bionic Decision Engine — The Universal Arbitrator
Compiled: 2026-05-11 (retroactive synthesis of 70+ protocols) Problem Class: Any "Should I?" question across all life domains — career, trades, purchases, relationships, time allocation. Axiom: "If you can't put a number on it, you can't decide on it. And if you decide on feelings, the wound decides for you (MP-8)."
When to Use
Invoke whenever the user faces a resource allocation decision. This includes:
- "Should I take this job/trade/client/deal?"
- "Is this worth the money/time/energy?"
- "Which option is better?"
- "Should I stay or leave?"
- Pricing questions (what to charge, what to pay)
- Any comparison of two or more alternatives
Solution Architecture
Gate 0: The Sunk Cost Purge (MP-14)
Before ANY analysis:
"Would I enter this position TODAY if I weren't already in it?"
If NO → the decision is already made. Skip to Exit Protocol. If YES → proceed to Gate 1.
Gate 1: Ruin Class Check (Law #1)
Does any option carry >5% probability of irreversible ruin across 5 domains?
| Domain | Ruin Threshold |
|---|---|
| Biological | Death, permanent disability |
| Legal | Incarceration, criminal record |
| Financial | Bankruptcy, total capital loss |
| Social | De-platforming, exile |
| Psychological | Burnout Stage 4, loss of agency |
VETO if P(Ruin) > 5%. No calculation needed. No exceptions.
Gate 2: The EEV Calculator (DEC-330 / DEC-526)
For each option, calculate Expected Economic Value:
EEV = P(success) × V(upside) − P(failure) × V(downside) − Friction Costs
Where:
P(success) = base rate for demographic × personal edge multiplier
V(upside) = monetary + optionality + compounding value
V(downside) = monetary loss + opportunity cost + psychological toll
Friction = time, energy, commute, complexity tax
Anti-Rationalization Rule (DEC-526): E(U) anchors MUST be activities you have actually paid for in the last 90 days. No hypotheticals.
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.
- 1mo ago First seen · 171 lines · 41 tokens per session scan A 452cabcbcdb4
bionic-decision-engine is a skill published in the GitHub repository winstonkoh87/Athena-Public (619 stars, last pushed today), licensed MIT. It adds 41 tokens to every session and 2,123 once invoked, about $0.0002 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.
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