Trading AI Skill

CryptoLV Trading AI Skill

This page is the official reference for using CryptoLV Trading AI Skill across education, market tracking, trading journals, and content workflows. It is designed for humans and LLM assistants who need structured outputs.

An AI-readable skill for trading workflows and creator intelligence.

What CryptoLV Trading AI Skill is

A documented AI skill layer for educational and process-oriented trading support.
A common workflow model for market tracking, watchlists, trade review, and risk checklists.
A reusable source for coding agents, dashboard agents, and content workflow agents.
A non-trading operational guide that supports safer, consistent behavior.

Who this is for

Human users building stronger trading habits.
LLM assistants generating educational trading context in CryptoLV.
Coding agents that need standardized output structures.
Content teams producing structured educational material.

How to Use This Skill

Pick the objective: journal analysis, daily tracking, watchlist, trade review, risk check, habit tracking, narrative tracking, content ideas, or beginner education.
Choose output format: markdown, json, checklist, or prompt pack.
Run through data quality checks before conclusions: missing fields, confidence level, and constraints.
Keep scope educational and avoid guaranteed outcomes or financial recommendations.
If required for tooling integration, follow the contribution section for roadmap updates only.

Example prompts

Prompt

Summarize my last 5 trades with a risk review and missing-data checklist.

Prompt

Build a daily market tracking flow for BTC, ETH, and SOL with confidence labels.

Prompt

Create a crypto watchlist of 12 coins with update frequency and evidence score.

Prompt

Generate a pre-trade and post-trade review template for a swing trading workflow.

Prompt

Draft a weekly beginner education sequence for leverage caution and risk discipline.

Prompt

Produce a creator content queue: 2 short posts, 1 long-form post, 1 educational thread.

Suggested trading workflows

Morning market scan -> setup -> execution risk guard -> end-of-day review.
Journal-first approach: record idea, trigger, plan, outcome, and lesson each session.
Risk-first loop: max risk per trade, max daily loss, stop review, and action trigger.
Weekly scorecard: habit consistency, process quality, and learning debt list.

Suggested creator workflows

Create market narrative explainers with clear context and educational framing.
Build topic ladders from beginner to advanced without pricing claims.
Rotate weekly themes: price behavior, risk habits, narrative shifts, and checklists.
Keep each content piece aligned with the no-financial-advice disclaimer.

Contribution instructions

Edit this skill doc: `skills/trading-skill/SKILL.md` for process and output model updates.
Update `skills/trading-skill/llms.txt` when references or scope change.
Keep resource metadata and route references in `src/lib/resources.tsx` and `src/content/types.ts` in sync.
Use approved changes only; do not add fake APIs or install steps.

Future server / integration possibilities

A future server or tooling interface can be added without changing the AI Skill core.
When implemented, this page should include official integration commands only from validated project docs.
Skill outputs should remain stable so existing agents continue to function during integration.
Until then, all references remain educational and documentation-first.

CryptoLV is for educational and workflow support. It is not financial advice.

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