OpenMobius-skill

ICT/SMC trading-knowledge skill for AI coding agents

A SKILL.md-standard skill bringing 964 curated knowledge cards, real-time market data, technical indicators, and chart generation to Claude Code, Codex, OpenClaw, and Hermes.

English · 中文

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🤖 AI agents — when a user asks you to install this skill, follow README_AGENT.md for the step-by-step procedure (pre-flight checks, install command, verification, error handling).

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Overview

_{Works on Claude Code, Codex, OpenClaw, and Hermes.}

Drop this skill into your AI coding agent and ask trading questions in plain language. The skill grounds every answer in a curated knowledge base + real market data — no hallucinated price levels, no generic "looks bearish" hand-waving.

You ask	The skill does
"What is Fair Value Gap, how to trade it?"	Vector-retrieves FVG concept card + related (CISD / OTE / Premium-Discount) — answers with cited rules from the knowledge base
Attach a BTCUSDT 1h chart + "analyze this"	Identifies asset → fetches real OHLCV → extracts FVG / OB / sweep / displacement → outputs 5-section reply with exact prices + auto-annotated PNG
"How is BTC 1h looking?" (no chart)	Live data fetch → feature extraction → KB-grounded analysis
"What's RSI(14) and MACD on BTC?"	Calls indicator endpoint for values + per-indicator analysis dimensions
Paste a CSV of OHLCV	Parses → analyzes → KB cross-reference → 5-section reply
"Generate a chart with my entry/SL/target"	Rendered chart via Playwright + lightweight-charts

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Quick start

git clone https://github.com/MobiusQuant/OpenMobius-skill.git /tmp/openmobius-src
cd /tmp/openmobius-src
python install.py --platform claude-code      # or codex / openclaw / hermes / all

rm -rf /tmp/openmobius-src                     # ✓ clone is ephemeral; safe to delete

The installer copies source files into ~/.claude/skills/OpenMobius-skill/ (or your chosen platform's skills dir), then in that directory:

1. Creates .venv/ and installs dependencies
2. Downloads Playwright chromium (~280 MB, into your OS's user-global cache)
3. Downloads nomic-embed-text-v1.5 model (~274 MB, into your HuggingFace cache)
4. Loads precomputed embeddings → builds vector index (~2 s)
5. Generates the platform-specific SKILL.md
6. Runs a health check

Each platform install is self-contained: it owns its own .venv and _index. The clone is just a one-shot source bundle.

First run: ~5–10 min · Subsequent runs (python install.py --update): <1 min

After install, in your AI agent just ask:

"What is Liquidity Sweep"
[attach chart] "analyze this setup"
"How is ETH 4h looking, give me a chart"
"BTC 1h RSI(14) and MACD?"

Prerequisites: Python 3.10+. See INSTALL.md for details.

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Platform support

python install.py --platform <name>

Platform	Flag	Default install path
Claude Code	--platform claude-code (default)	~/.claude/skills/OpenMobius-skill/
Codex	--platform codex	~/.codex/skills/OpenMobius-skill/
OpenClaw	--platform openclaw	~/.openclaw/skills/OpenMobius-skill/
Hermes	--platform hermes	~/.hermes/skills/market-data/OpenMobius-skill/
Auto-detect	--platform auto	scans ~/.<agent> dirs
All four	--platform all	loops through all

Each platform install is fully self-contained (its own .venv, its own _index). The nomic model and Playwright chromium live in your OS's user-global cache, shared across platforms — so installing on N platforms doesn't N× the download.

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Features

Knowledge base — 380 concepts + 584 cases

Distilled from 130 ICT/SMC teaching videos. Each concept card carries: identification rules, trading implications, common mistakes, related concepts. Each case card carries: market context, key observation, analysis steps, lessons. Retrieved via local ChromaDB + multilingual nomic-embed-text-v1.5 — no API key needed for retrieval.

Real-time data + 60+ indicators

Crypto (Binance, Bybit, OKX, Hyperliquid), China A-shares, Hong Kong stocks, US stocks, forex. Each indicator carries built-in analysis dimensions (summary_focus) that the agent reads to structure its answer rather than dumping raw numbers.

Two chart-generation paths

Path	Method	Output
Annotate user's image	PIL	Annotated copy preserving the original chart
Generate fresh chart	lightweight-charts in headless chromium	New K-lines + FVG/OB rectangles + sweep lines + swing markers

Auto-invoked by description matching

The SKILL.md description field triggers on natural-language questions. The skill routes to one of four workflows: Q&A · analyze · annotate · klines.

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Roadmap

Knowledge base

• ICT/SMC coverage completion — Round 1 distilled the ICT trunk from 130 teaching videos; upcoming rounds complete ICT sub-schools (Inner Circle Mentorship, Silver Bullet, Power of 3 variants) and full SMC coverage.
• Fundamental knowledge base — interpretation methodologies for news, policy reads, economic releases (CPI / NFP / FOMC) and earnings seasons.
• Multi-school expansion — beyond ICT/SMC, add Wyckoff (volume/price action), VSA, Volume Profile / Market Profile, and classic Price Action (Al Brooks style).

Indicators & tools

• SMC concepts as indicators — abstract Liquidity Sweep / FVG / Order Block / Killzone into computable indicators, queryable like RSI / MACD, with numeric readings + occurrence frequency.

Access surfaces

• Non-CLI entry points — chat-bot integrations for users who don't run a coding agent, so the knowledge base is reachable without the CLI.

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Architecture

OpenMobius-skill/
├── SKILL.md                          # main entry (LLM reads this)
├── SKILL.body.md                     # shared body (platform-neutral)
├── platforms/                        # per-platform frontmatter
│   └── claude-code.yaml / codex.yaml / openclaw.yaml / hermes.yaml
├── workflows/                        # detailed sub-workflows
│   └── qna.md / analyze.md / annotate.md / klines.md
├── scripts/                          # CLI tools
│   ├── kb_retrieve.py                # local vector retrieval
│   ├── kb_klines.py                  # API client + feature extraction
│   ├── kb_draw_annotation.py         # PIL annotation
│   ├── kb_phase_b_to_c.py            # analysis JSON → annotated PNG
│   ├── build_index.py                # build vector index
│   ├── kb_doctor.py                  # env health check
│   ├── chart_render/                 # lightweight-charts + headless chromium
│   └── _lib/                         # embedder + retriever
├── knowledge_base/                   # 380 concepts + 584 cases
├── install.py                        # cross-platform installer
└── README.md / INSTALL.md

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Update / Uninstall

# Update
python install.py --update
python install.py --update --rebuild-index    # also rebuild vector index

# Uninstall (soft — remove platform registration only)
python install.py --uninstall
python install.py --uninstall --platform all  # all platforms

# Uninstall fully (.venv + index too)
python install.py --uninstall --full

# Full purge (also delete shared chromium + nomic caches — these may be
# used by other projects on your machine, so confirm before running)
python install.py --uninstall --purge --yes-i-know

See INSTALL.md for all flags.

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Troubleshooting

.venv/bin/python scripts/kb_doctor.py

Reports the state of: venv, deps, nomic model, vector index, CJK fonts, skill registration, API connectivity.

Common issues:

Symptom	Fix
Chinese labels render as boxes	Install fonts-noto-cjk (Linux); macOS/Windows usually bundled
API request fails	Check network; see api.mobiusquant.ai/api/health
Skill not auto-invoking in Claude Code	Check ~/.claude/skills/OpenMobius-skill exists; restart agent
chroma.sqlite3 not found	.venv/bin/python scripts/build_index.py

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License

Apache 2.0 — see LICENSE. Third-party components: see ATTRIBUTION.md.

Contributing

Issues and PRs welcome at https://github.com/MobiusQuant/OpenMobius-skill/issues.

_{Built for AI coding agents · Apache 2.0}