custom-indicators

Name: custom-indicators
Author: agiprolabs

235stars53forks

How to install custom-indicators?

agiprolabs/claude-trading-skills/custom-indicators

$npx -y skills add agiprolabs/claude-trading-skills --skill custom-indicators

Installs into the current project.

Summary

Crypto-native indicators including NVT ratio, exchange flow, funding rate signals, holder momentum, and smart money flow

Files · 1

View on GitHub

SKILL.md

1	# Custom Crypto Indicators
2
3	## Why Standard TA Falls Short for Crypto
4
5	Traditional technical analysis was built for equities and forex — markets with
6	fixed supply, regulated exchanges, and institutional-dominated order flow.
7	Crypto markets have unique properties that demand purpose-built indicators:
8
9	- On-chain transparency: Every transaction is public. We can measure real
10	economic activity, not just price and volume on a single exchange.
11	- Supply mechanics: Fixed or programmatic supply schedules make
12	supply-side analysis (velocity, holder distribution) meaningful.
13	- Derivatives dominance: Perpetual futures funding rates and open interest
14	often drive spot price, not the other way around.
15	- Whale concentration: A small number of wallets hold outsized supply.
16	Tracking their behavior provides alpha that equity-market TA cannot.
17	- Exchange flows: On-chain deposit/withdrawal to centralized exchanges
18	signals intent to sell or accumulate.
19
20	This skill covers nine crypto-native indicators. Each section includes the
21	formula, interpretation guide, data sources, and a working code snippet.
22
23	## Files
24
25	\| File \| Description \|
26	\|------\|-------------\|
27	\| `references/indicator_formulas.md` \| Full formulas, parameter tables, signal ranges for all 9 indicators \|
28	\| `references/signal_interpretation.md` \| Composite scoring, divergence detection, false signal filtering \|
29	\| `scripts/compute_crypto_indicators.py` \| Computes all 9 indicators from free APIs or demo data \|
30	\| `scripts/holder_momentum.py` \| Holder count tracking with momentum signals \|
31
32	---
33
34	## Indicator 1: NVT Ratio
35
36	Network Value to Transactions — the crypto equivalent of a P/E ratio.
37
38	```
39	NVT = Market Cap / Daily On-Chain Transaction Volume (USD)
40	```
41
42	- High NVT (> 65): Network is overvalued relative to its economic
43	throughput. Bearish signal.
44	- Low NVT (< 25): Network is undervalued or seeing heavy real usage.
45	Bullish signal.
46	- Data sources: CoinGecko (market cap), blockchain explorers or
47	DeFiLlama (transaction volume).
48
49	```python
50	def nvt_ratio(market_cap: float, daily_tx_volume_usd: float) -> float:
51	"""Compute NVT ratio.
52
53	Args:
54	market_cap: Current market capitalization in USD.
55	daily_tx_volume_usd: 24h on-chain transaction volume in USD.
56
57	Returns:
58	NVT ratio value.
59	"""
60	if daily_tx_volume_usd <= 0:
61	return float("inf")
62	return market_cap / daily_tx_volume_usd
63	```
64
65	Smoothing: Apply a 14-day or 28-day moving average to NVT (called
66	NVT Signal) to reduce noise from daily volume spikes.
67
68	---
69
70	## Indicator 2: MVRV Ratio
71
72	Market Value to Realized Value — compares the current market cap to the
73	aggregate cost basis of all holders.
74
75	```
76	MVRV = Market Cap / Realized Cap
77	Realized Cap = Sum of (each UTXO * price when it last moved)
78	```
79
80	- MVRV > 3.5: Most holders are in deep profit. Distribution likely.
81	- MVRV < 1.0: Most holders are underwater. Historically marks bottoms.
82	- Data sources: Glassnode, CryptoQuant (Bitcoin/Ethereum). For Solana
83	tokens, approximate via average entry price of top holders.
84
85	```python
86	def mvrv_ratio(market_cap: float, realized_cap: float) -> float:
87	"""Compute MVRV ratio.
88
89	Args:
90	market_cap: Current market capitalization in USD.
91	realized_cap: Realized capitalization (aggregate cost basis).
92
93	Returns:
94	MVRV ratio value.
95	"""
96	if realized_cap <= 0:
97	return float("inf")
98	return market_cap / realized_cap
99	```
100
101	For tokens without UTXO-based realized cap, estimate using average purchase
102	price from DEX trade history multiplied by circulating supply.
103
104	---
105
106	## Indicator 3: Exchange Flow
107
108	Net exchange deposits minus withdrawals — signals selling or accumulation
109	intent.
110
111	```
112	Exchange Netflow = Deposits to Exchanges - Withdrawals from Exchanges
113	```
114
115	- Positive netflow (large deposits): Holders moving tokens to exchanges,
116	likely to sell. Bearish.
117	- Negative netflow (withdrawals): Tokens leaving exchanges to cold
118	storage. Bullish accumulation signal.
119	- Data sources: CryptoQuant, Glassnode. For Solana SPL tokens, track
120	transfers to known exchange wallets via Helius or Solana RPC.
121
122	```python
123	def exchange_netflow(
124	deposits_usd: float, withdrawals_usd: float
125	) -> tuple[float, str]:
126	"""Compute exchange netflow and interpret.
127
128	Returns:
129	Tuple of (netflow_value, signal_label).
130	"""
131	netflow = deposits_usd - withdrawals_usd
132	if netflow > 0:
133	signal = "bearish"
134	elif netflow < 0:
135	signal = "bullish"
136	else:
137	signal = "neutral"
138	return netflow, signal
139	```
140
141	Normalize by market cap for cross-token comparison:
142	`Netflow Ratio = Netflow / Market Cap`.
143
144	---
145
146	## Indicator 4: Funding Rate Signal
147
148	Perpetual futures contracts use funding rates to anchor price to spot.
149
150	```
151	Fun

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custom-indicators

235stars53forks

View on GitHub

How to install custom-indicators?

agiprolabs/claude-trading-skills/custom-indicators

$npx -y skills add agiprolabs/claude-trading-skills --skill custom-indicators

Installs into the current project.

Summary

Crypto-native indicators including NVT ratio, exchange flow, funding rate signals, holder momentum, and smart money flow

Files · 1

View on GitHub

SKILL.md

1	# Custom Crypto Indicators
2
3	## Why Standard TA Falls Short for Crypto
4
5	Traditional technical analysis was built for equities and forex — markets with
6	fixed supply, regulated exchanges, and institutional-dominated order flow.
7	Crypto markets have unique properties that demand purpose-built indicators:
8
9	- On-chain transparency: Every transaction is public. We can measure real
10	economic activity, not just price and volume on a single exchange.
11	- Supply mechanics: Fixed or programmatic supply schedules make
12	supply-side analysis (velocity, holder distribution) meaningful.
13	- Derivatives dominance: Perpetual futures funding rates and open interest
14	often drive spot price, not the other way around.
15	- Whale concentration: A small number of wallets hold outsized supply.
16	Tracking their behavior provides alpha that equity-market TA cannot.
17	- Exchange flows: On-chain deposit/withdrawal to centralized exchanges
18	signals intent to sell or accumulate.
19
20	This skill covers nine crypto-native indicators. Each section includes the
21	formula, interpretation guide, data sources, and a working code snippet.
22
23	## Files
24
25	\| File \| Description \|
26	\|------\|-------------\|
27	\| `references/indicator_formulas.md` \| Full formulas, parameter tables, signal ranges for all 9 indicators \|
28	\| `references/signal_interpretation.md` \| Composite scoring, divergence detection, false signal filtering \|
29	\| `scripts/compute_crypto_indicators.py` \| Computes all 9 indicators from free APIs or demo data \|
30	\| `scripts/holder_momentum.py` \| Holder count tracking with momentum signals \|
31
32	---
33
34	## Indicator 1: NVT Ratio
35
36	Network Value to Transactions — the crypto equivalent of a P/E ratio.
37
38	```
39	NVT = Market Cap / Daily On-Chain Transaction Volume (USD)
40	```
41
42	- High NVT (> 65): Network is overvalued relative to its economic
43	throughput. Bearish signal.
44	- Low NVT (< 25): Network is undervalued or seeing heavy real usage.
45	Bullish signal.
46	- Data sources: CoinGecko (market cap), blockchain explorers or
47	DeFiLlama (transaction volume).
48
49	```python
50	def nvt_ratio(market_cap: float, daily_tx_volume_usd: float) -> float:
51	"""Compute NVT ratio.
52
53	Args:
54	market_cap: Current market capitalization in USD.
55	daily_tx_volume_usd: 24h on-chain transaction volume in USD.
56
57	Returns:
58	NVT ratio value.
59	"""
60	if daily_tx_volume_usd <= 0:
61	return float("inf")
62	return market_cap / daily_tx_volume_usd
63	```
64
65	Smoothing: Apply a 14-day or 28-day moving average to NVT (called
66	NVT Signal) to reduce noise from daily volume spikes.
67
68	---
69
70	## Indicator 2: MVRV Ratio
71
72	Market Value to Realized Value — compares the current market cap to the
73	aggregate cost basis of all holders.
74
75	```
76	MVRV = Market Cap / Realized Cap
77	Realized Cap = Sum of (each UTXO * price when it last moved)
78	```
79
80	- MVRV > 3.5: Most holders are in deep profit. Distribution likely.
81	- MVRV < 1.0: Most holders are underwater. Historically marks bottoms.
82	- Data sources: Glassnode, CryptoQuant (Bitcoin/Ethereum). For Solana
83	tokens, approximate via average entry price of top holders.
84
85	```python
86	def mvrv_ratio(market_cap: float, realized_cap: float) -> float:
87	"""Compute MVRV ratio.
88
89	Args:
90	market_cap: Current market capitalization in USD.
91	realized_cap: Realized capitalization (aggregate cost basis).
92
93	Returns:
94	MVRV ratio value.
95	"""
96	if realized_cap <= 0:
97	return float("inf")
98	return market_cap / realized_cap
99	```
100
101	For tokens without UTXO-based realized cap, estimate using average purchase
102	price from DEX trade history multiplied by circulating supply.
103
104	---
105
106	## Indicator 3: Exchange Flow
107
108	Net exchange deposits minus withdrawals — signals selling or accumulation
109	intent.
110
111	```
112	Exchange Netflow = Deposits to Exchanges - Withdrawals from Exchanges
113	```
114
115	- Positive netflow (large deposits): Holders moving tokens to exchanges,
116	likely to sell. Bearish.
117	- Negative netflow (withdrawals): Tokens leaving exchanges to cold
118	storage. Bullish accumulation signal.
119	- Data sources: CryptoQuant, Glassnode. For Solana SPL tokens, track
120	transfers to known exchange wallets via Helius or Solana RPC.
121
122	```python
123	def exchange_netflow(
124	deposits_usd: float, withdrawals_usd: float
125	) -> tuple[float, str]:
126	"""Compute exchange netflow and interpret.
127
128	Returns:
129	Tuple of (netflow_value, signal_label).
130	"""
131	netflow = deposits_usd - withdrawals_usd
132	if netflow > 0:
133	signal = "bearish"
134	elif netflow < 0:
135	signal = "bullish"
136	else:
137	signal = "neutral"
138	return netflow, signal
139	```
140
141	Normalize by market cap for cross-token comparison:
142	`Netflow Ratio = Netflow / Market Cap`.
143
144	---
145
146	## Indicator 4: Funding Rate Signal
147
148	Perpetual futures contracts use funding rates to anchor price to spot.
149
150	```
151	Fun

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