custom-indicators
Crypto-native indicators including NVT ratio, exchange flow, funding rate signals, holder momentum, and smart money flow
Skill by Serennity007
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/serennity007-custom-indicators
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: finance
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 3
api.coingecko.com· found in codeapi.llama.fi· found in codecodeload.github.com· found in install command
Files it touches
~/.claude/skills/custom-indicators
What's inside
- Skill name
custom-indicators- Description
- Crypto-native indicators including NVT ratio, exchange flow, funding rate signals, holder momentum, and smart money flow
- License
- MIT
- Instructions
- 395 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (5)
- SKILL.md
- indicator_formulas.md · references/
- signal_interpretation.md · references/
- compute_crypto_indicators.py · scripts/
- holder_momentum.py · scripts/
SKILL.md (first lines)
# Custom Crypto Indicators
## Why Standard TA Falls Short for Crypto
Traditional technical analysis was built for equities and forex — markets with
fixed supply, regulated exchanges, and institutional-dominated order flow.
Crypto markets have unique properties that demand purpose-built indicators:
- **On-chain transparency**: Every transaction is public. We can measure real
economic activity, not just price and volume on a single exchange.
- **Supply mechanics**: Fixed or programmatic supply schedules make
supply-side analysis (velocity, holder distribution) meaningful.
- **Derivatives dominance**: Perpetual futures funding rates and open interest
often drive spot price, not the other way around.
- **Whale concentration**: A small number of wallets hold outsized supply.
Tracking their behavior provides alpha that equity-market TA cannot.
- **Exchange flows**: On-chain deposit/withdrawal to centralized exchanges
signals intent to sell or accumulate.
This skill covers nine crypto-native indicators. Each section includes the
formula, interpretation guide, data sources, and a working code snippet.
## Files
| File | Description |
|------|-------------|
| `references/indicator_formulas.md` | Full formulas, parameter tables, signal ranges for all 9 indicators |
| `references/signal_interpretation.md` | Composite scoring, divergence detection, false signal filtering |
| `scripts/compute_crypto_indicators.py` | Computes all 9 indicators from free APIs or demo data |
| `scripts/holder_momentum.py` | Holder count tracking with momentum signals |
---
## Indicator 1: NVT Ratio
**Network Value to Transactions** — the crypto equivalent of a P/E ratio.
```
NVT = Market Cap / Daily On-Chain Transaction Volume (USD)
```
- **High NVT (> 65)**: Network is overvalued relative to its economic
throughput. Bearish signal.
- **Low NVT (< 25)**: Network is undervalued or seeing heavy real usage.
Bullish signal.
- **Data sources**: CoinGecko (market cap), blockchain explorers or
DeFiLlama (transaction volume).
```python
def nvt_ratio(market_cap: float, daily_tx_volume_usd: float) -> float:
"""Compute NVT ratio.
Args:
market_cap: Current market capitalization in USD.
daily_tx_volume_usd: 24h on-chain transaction volume in USD.
Returns:
NVT ratio value.
"""
if daily_tx_volume_usd <= 0:
return float("inf")
return market_cap / daily_tx_volume_usd
```
**Smoothing**: Apply a 14-day or 28-day moving average to NVT (called
NVT Signal) to reduce noise from daily volume spikes.
---
## Indicator 2: MVRV Ratio
**Market Value to Realized Value** — compares the current market cap to the
aggregate cost basis of all holders.
```
MVRV = Market Cap / Realized Cap
Realized Cap = Sum of (each UTXO * price when it last moved)
```
- **MVRV > 3.5**: Most holders are in deep profit. Distribution likely.
- **MVRV < 1.0**: Most holders are underwater. Historically marks bottoms.
- **Data sources**: Glassnode, CryptoQuant (Bitcoin/Ethereum). For Solana
tokens, approximate via average entry price of top holders.
```python
def mvrv_ratio(market_cap: float, realized_cap: float) -> float:
"""Compute MVRV ratio.
Args:
market_cap: Current market capitalization in USD.
realized_cap: Realized capitalization (aggregate cost basis).
Returns:
MVRV ratio value.
"""
if realized_cap <= 0:
return float("inf")
return market_cap / realized_cap
```
For tokens without UTXO-based realized cap, estimate using average purchase
price from DEX trade history multiplied by circulating supply.
---
## Indicator 3: Exchange Flow
**Net exchange deposits minus withdrawals** — signals selling or accumulation
intent.
```
Exchange Netflow = Deposits to Exchanges - Withdrawals from Exchanges
```
- **Positive netflow (large deposits)**: Holders moving tokens to exchanges,
likely to sell. Bearish.
- **Negative netflow (withdrawals)**: Tokens leaving exchanges to cold
storage. Bullish accumulation signal.
- **Data sources**: CryptoQuant, Glassnode. For Solana SPL tokens, trackFrom Serennity007/awesome-stock-quant-skills, MIT.
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Signals
- Stars
- 41
- Forks
- 8
- Open issues
- 1
- Last commit (this folder)
- Aug 25, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
custom-indicators skill. Agent Mart. https://agentmart.dev/skills/serennity007-custom-indicators (last updated 2026-10-24)