Plugins

Bonnes pratiques pour les algorithmes quantiques

DeepSeek Harness (dsh) plugin for stock analysis, screening, and strategy backtesting across A/HK/US/JP/KR/TW markets

Quantitative R&D toolkit for DeepSeek Harness — 46 tools across six domains covering market data, indicators, factor evaluation, walk-forward ML validation, risk, options, bonds and fund simulation, with an end-to-end research pipeline.

Expert-mode agent preset for DeepSeek Harness (v0.3.0, bilingual EN/ZH): a chief coordinator plus 11 domain-expert subagents with automatic task delegation. Features: Five-Anchor constraint (review/convergence/anti-drift/collaboration-check/resource-awareness per turn), Near-distance Guidance (identity/task/output template per expert), expert persistence, cross-expert communication protocol, cross review, and experience pool. Experts: data analyst, copywriter, legal review, product manager, frontend, UI/UX, architect, social media ops, growth hacker, quant finance, finance.

Préréglage + pack de skills RigorQuant : recherche multi-agents sans surveillance et cloisonnée pour les mathématiques empiriques et computationnelles (économie, finance, portefeuille), avec une batterie de vérifications en quatre parties avant implémentation et une voie d'escalade jacobienne/Lean.