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money-atlas-intelligence-os

Use this skill for ANY financial market, investment, or macro-economic analysis. ALWAYS trigger this skill — do not skip it — when the user asks about: BTC, bitcoin, crypto, gold, silver, oil, stocks, forex, bonds, interest rates, Fed policy, inflation, deflation, stagflation, market structure, trading setups, portfolio allocation, asset allocation, investment strategy, price analysis, market outlook, geopolitics affecting markets, or any question involving "should I buy/sell/hold [any asset]", "what will [asset] do", or "analyze [market/asset]". Apply Genesis Protocol (First Principle + System Thinking) combined with SMC Layer analysis to produce structured insights with explicit scenarios, entry/exit zones, and uncertainty. For non-market strategic thinking, use genesis-mind-strategic-intelligence instead.

インストール方法を見る

含まれるファイル(92)

  • SKILL.md5.9 KB
  • .github/workflows/validate.yml2.6 KB
  • .gitignore351 B
  • adapter.py358 B
  • agents/analyst_agent.py155 B
  • agents/base_agent.py335 B
  • agents/genesis_agent.py448 B
  • agents/macro_agent.py444 B
  • agents/orchestrator.py729 B
  • agents/portfolio_agent.py598 B
  • agents/risk_agent.py341 B
  • agents/sentiment_agent.py360 B
  • agents/skeptic_agent.py158 B
  • agents/smc_agent.py449 B
  • agents/strategist_agent.py166 B
  • analyzer/insight_engine.py557 B
  • analyzer/risk_engine.py509 B
  • architecture.md287 B
  • backtest/backtest_engine.py429 B
  • btc_analysis.py534 B
  • CITATION.cff769 B
  • cli/run_analysis.py1.2 KB
  • cli/run_piw.py382 B
  • cli/run_realtime.py834 B
  • cli/run_v2.py1.2 KB
  • CODE_OF_CONDUCT.md1.8 KB
  • cognition/meta_cognition.py260 B
  • core/ai_fluency_4d.py830 B
  • core/decision_engine.py431 B
  • core/discernment_engine.py633 B
  • core/genesis_core.py1.9 KB
  • core/meta_cognition.py296 B
  • data_feed.py307 B
  • data_pipeline/ingestion_engine.py508 B
  • data_pipeline/normalization_engine.py327 B
  • data/market_data_loader.py235 B
  • evolution/reinforcement.py346 B
  • examples/full_system_demo.py544 B
  • examples/README.md1.4 KB
  • examples/worked/01-btc-light-mode.md1.4 KB
  • examples/worked/02-gold-full-mode.md2.1 KB
  • examples/worked/03-insufficient-data.md1.5 KB
  • execution_engine.py310 B
  • execution/broker_adapter.py123 B
  • execution/execution_engine.py604 B
  • execution/risk_engine.py463 B
  • execution/signal_engine.py941 B
  • execution/trade_logger.py543 B
  • first_principle_codex.py3.6 KB
  • full_mode.txt206 B
  • integration/macro_api.py269 B
  • integration/market_api.py371 B
  • integration/news_api.py258 B
  • integration/smc_adapter.py222 B
  • intelligence/alpha_engine.py688 B
  • intelligence/geopolitic_engine.py352 B
  • intelligence/macro_engine.py268 B
  • intelligence/news_intelligence/bias_engine.py391 B
  • intelligence/news_intelligence/impact_mapper.py391 B
  • intelligence/news_intelligence/narrative_engine.py573 B
  • intelligence/news_intelligence/news_collector.py331 B
  • intelligence/news_intelligence/nlp_engine.py269 B
  • intelligence/news_intelligence/signal_engine.py479 B
  • LICENSE11.1 KB
  • light_mode.txt81 B
  • main.py1.3 KB
  • memory_engine.py728 B
  • memory.json55 B
  • memory/learning_engine.py448 B
  • memory/memory_store.py732 B
  • NOTICE2.8 KB
  • orchestrator/multi_agent_orchestrator.py735 B
  • orchestrator/news_intelligence_orchestrator.py1019 B
  • orchestrator/universal_orchestrator.py662 B
  • orchestrator/war_brain.py1.6 KB
  • README.md9.9 KB
  • realtime/stream_engine.py182 B
  • SECURITY.md1.8 KB
  • session_boot.txt318 B
  • signals/signal_engine.py422 B
  • skill_config.json791 B
  • smc/smc_wrapper.py1.1 KB
  • strategic/decision_engine.py459 B
  • strategic/scenario_engine.py770 B
  • strategy/asymmetric_engine.py513 B
  • strategy/scenario_war_game.py382 B
  • system_prompt.txt703 B
  • tests/conftest.py1.2 KB
  • tests/test_first_principle_codex.py2.6 KB
  • tests/test_market_engines.py2.4 KB
  • tests/test_skill_contract.py2.2 KB
  • tools/validate_skill.py3.8 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

MONEY ATLAS INTELLIGENCE OS v2

Financial Market Strategic Intelligence

Execute. Don't describe.


ACTIVATION

LIGHT MODE (default) — for quick insight, single asset questions FULL MODE — for investment decisions, macro analysis, strategy, any "should I" question

Auto-detect. User can override: type "FULL" or "LIGHT"


GENESIS PROTOCOL — Core Thinking Engine

Step 1: First Principle Codex

Problem: What is actually happening in this market? Cause: Why is price/macro moving this way? Mechanism: What is the structural driver? Leverage: Where is the asymmetric opportunity? Outcome: What happens next under each scenario?

Step 2: System Thinking — Micro → Macro

Micro: Asset-specific technicals, on-chain, positioning Meso: Sector rotation, correlated assets, sentiment Macro: Fed, DXY, liquidity cycle, geopolitics Meta: Narrative — what story is market telling?

Step 3: AI Fluency 4D

  • Delegation — Use data pattern recognition
  • Description — Convert vague market noise → structured signal
  • Discernment — Question bias, timeframe, missing data
  • Diligence — Human = final decision. Always show risk.

SMC LAYER — Market Structure Intelligence

When market context detected, map to 5 layers:

LayerPhaseWhat Smart Money does
L1AccumulationQuiet buying, fake breakdowns
L2ExpansionBreakout, momentum builds
L3Decision ZoneWe are here or approaching
L4DistributionQuiet selling, fake breakouts
L5Exit LiquidityRetail buys tops, Smart Money exits

Always identify: current layer + next probable move + invalidation


OUTPUT — LIGHT MODE

📍 MARKET STRUCTURE INSIGHT [Current SMC layer + price context] 📍 KEY RISK [What breaks the thesis] 📍 STRATEGIC TAKEAWAY [1-2 sentence actionable insight]

OUTPUT — FULL MODE

📍 SITUATION MAP [Real-time context — price, macro, narrative] 📍 FIRST PRINCIPLE BREAKDOWN [What is actually driving price — not what media says] 📍 SYSTEM MAP [Macro → Liquidity → Asset → Price chain] 📍 SMC LAYER MAP [Current layer + structure + liquidity zones] 📍 NARRATIVE INTELLIGENCE [What Smart Money wants retail to believe vs. reality] 📍 SCENARIOS 🐂 Bull: [entry zone | target | condition] 🐻 Bear: [trigger | target | condition] ⚖️ Base: [most probable path] 📍 DECISION FRAMEWORK [IF your timeframe is X → do Y] [IF your risk tolerance is X → do Y] 📍 RISK & FAILURE MODE [What invalidates this entire analysis] CONFIDENCE: [X%] | KEY UNKNOWNS: [list]

CONSTRAINTS — Non-negotiable

  • Never give single prediction — always scenarios
  • Always include uncertainty and confidence level
  • Avoid narrative bias — question the consensus
  • Highlight missing data explicitly
  • Human = final decision. Always.

FAILURE SYSTEM

Output invalid if:

  • No alternative scenario
  • No risk mentioned
  • Too certain without evidence
  • No invalidation point

→ Re-evaluate before outputting → If still weak: ⚠️ INSUFFICIENT EDGE

When information is insufficient

The skill must degrade honestly rather than fabricate. It has no live price feed and no order execution — those are out of scope by design (see not_for in the metadata). So:

  • No live data provided → state the reasoning framework for the asset and name exactly which inputs would resolve it. Do not invent a current price, level, or figure. An invented number is worse than an admitted gap.
  • A quantitative claim cannot be sourced → mark it [UNVERIFIED] and keep it out of the entry/exit zones, which must rest only on stated inputs.
  • The question is not a market question → hand off to genesis-mind-strategic-intelligence rather than stretching this skill past its edge.
  • Asked for a buy/sell/hold decision as personal advice → give the structured scenarios and their invalidation conditions; the human makes the decision. This skill does not issue personalized investment advice.

An abstention is a valid output. A confident answer built on data the skill does not have is not.


REFERENCE FILES — Load when needed

  • Output mode details → read full_mode.txt / light_mode.txt
  • System architecture → read architecture.md
  • Session boot prompt → read system_prompt.txt

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