Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Translate trading strategies between different frameworks and languages. Use when converting Pine Script to Python, porting strategies to NautilusTrader, or...
Translate trading strategies between different frameworks and languages. Use when converting Pine Script to Python, porting strategies to NautilusTrader, or...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Source: https://mcpmarket.com/tools/skills/strategy-translator
You need to apply this capability as part of trading research workflows (data, features, backtests, ML, reporting). You want a reproducible output that can be committed to this repo (code, configs, docs).
Objective: what success looks like (metric, constraints, time horizon). Data: symbols, timeframe, sampling, data sources, and leakage risks. Constraints: compute budget, latency, interpretability, and deployment requirements.
A concrete plan (steps + checks). A minimal implementation sketch (files to create/change) and verification steps. If applicable: a risk checklist (leakage, overfitting, evaluation pitfalls).
Restate the task in measurable terms. Enumerate required artifacts (datasets, features, configs, scripts, reports). Propose a default approach and 1-2 alternatives. Add validation gates (walk-forward, Monte Carlo, sanity checks). Produce repo-ready deliverables (code + docs) and a run command.
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.