The DECISION LENS for trading peers — recalls the CURRENT signal snapshot per market from the live ledger and renders it through the sim arsenal off ONE call: quantum factor-circuit order-optimal sequencing + decision-sim CVaR-robust sizing, sized against the MEASURED per-factor edge (from the edge-audit), correlation-aware. Emits an actionable call per market {side, sizePct, confidence, sequence}. Flat/zero-size when there is no measured edge after cost — the honest default. Sibling of trade...
Scanned 9/10/2026
Install to Claude Code
npx -y skills add nexuslinkproductions/yuri-os --skill trade-decision-sim --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Trade Decision Sim?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/nexuslinkproductions-trade-decision-sim)More formats (shields.io, HTML) on the badges page.
---
name: trade-decision-sim
description: "The DECISION LENS for trading peers — recalls the CURRENT signal snapshot per market from the live ledger and renders it through the sim arsenal off ONE call: quantum factor-circuit order-optimal sequencing + decision-sim CVaR-robust sizing, sized against the MEASURED per-factor edge (from the edge-audit), correlation-aware. Emits an actionable call per market {side, sizePct, confidence, sequence}. Flat/zero-size when there is no measured edge after cost — the honest default. Sibling of trade-edge-audit (the EDGE lens); the trade-engine analog of quantum-hypothesis-simulation for a live decision."
---
<!-- GENERATED:YURI-CODEX-SKILL-ADAPTER:v1 -->
# YURI skill adapter
Authoritative source: `skills/trade-decision-sim/SKILL.md`
Authoritative source SHA-256: `89d9e6ed6c5e59f7e23b5d43012739426f2bff34209def2258dbe0446753860e`
Source class: `canonical`
Before acting, read the authoritative source file above completely from beginning to end. If the governed source is absent, run `node _SYSTEM/Scripts/skill-recall.mjs --show trade-decision-sim` and read its complete verified output. Follow that source as the skill body; this adapter is a non-authoritative metadata-and-pointer projection.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
This skill provides comprehensive analysis of competitor SEO and GEO strategies, revealing what's working in your market and identifying opportunities to outperform the competition.
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review...
Use when an operation issue is a Paperclip cursor-window, distill, or backfill — `operationType: "distill"` or `"backfill"` and the body references a Paperclip source bundle for a project or root issue. Turn raw Paperclip activity into a wiki-insightful project page, decisions log, and history note. This skill exists specifically to replace the stiff, datestamp-heavy templated output that the deterministic distiller produces.
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publi...
Semantic search, similar content discovery, and structured research using Exa API