scalping-strategy

Name: scalping-strategy
Author: SKE-Labs

15stars2forks

How to install scalping-strategy?

ske-labs/agent-trading-skills/scalping-strategy

$npx -y skills add SKE-Labs/agent-trading-skills --skill scalping-strategy

Installs into the current project.

Summary

Evaluate and plan very short-horizon trades in highly liquid markets. Use when the user needs an executable scalp with latency, spread, fee, slippage, and capacity controls.

Files · 1

View on GitHub

SKILL.md

1	# Scalping Strategy
2
3	Target small, frequent profits from minimal price movements on 1m-5m timeframes.
4
5	## Setup Conditions
6
7	\| Factor \| Requirement \|
8	\| --- \| --- \|
9	\| Data \| Timestamped quotes/trades plus closed bars \|
10	\| Cost gate \| Expected gross edge exceeds spread, fees, slippage, and adverse selection \|
11	\| Liquidity \| Tested depth, order size, fill rate, and cancellation behavior \|
12	\| Risk \| Hard per-trade and session loss limits from the portfolio mandate \|
13	\| Deployment \| Positive held-out expectancy in the intended venue and session \|
14
15	## Scalping Techniques
16
17	### 1. Momentum Scalping
18
19	Enter on strong momentum candles on 1m, ride for small gain, exit immediately on momentum loss.
20
21	```
22	get_indicators(indicator_code="rsi", symbol=<symbol>, exchange=<exchange>, interval="1m")
23	get_indicators(indicator_code="macd", symbol=<symbol>, exchange=<exchange>, interval="1m")
24	```
25
26	Define an objective closed-bar momentum trigger and exit. RSI/MACD are correlated price transforms; retain them only if they improve held-out net results over a price-only baseline.
27
28	### 2. Level Scalping
29
30	Quick bounces at key S/R levels with tight stops.
31
32	```
33	get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval="5m", date=<date>)
34	```
35
36	Identify levels on the context timeframe, define a numerical rejection on the execution timeframe, and place invalidation beyond the level plus expected stop slippage. Require the planned payoff to remain positive after costs.
37
38	### 3. Range Scalping
39
40	Buy support, sell resistance within a defined micro-range. Repeat until range breaks.
41
42	```
43	get_indicators(indicator_code="dmi", symbol=<symbol>, exchange=<exchange>, interval="5m")
44	```
45
46	Use a calibrated range classifier; ADX alone does not confirm a micro-range. Stop applying the rule when the closed-bar invalidation or liquidity gate fails.
47
48	## Workflow
49
50	### 1. Confirm Direction on 5m
51
52	```
53	get_indicators(indicator_code="ema", symbol=<symbol>, exchange=<exchange>, interval="5m")
54	get_indicators(indicator_code="dmi", symbol=<symbol>, exchange=<exchange>, interval="5m")
55	```
56
57	Establish bias from higher timeframe before scalping on 1m.
58
59	### 2. Identify Setup on 1m
60
61	```
62	get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval="1m", date=<date>)
63	get_indicators(indicator_code="rsi", symbol=<symbol>, exchange=<exchange>, interval="1m")
64	```
65
66	Pick one technique (momentum, level, or range) based on current conditions.
67
68	### 3. Mark Key Levels
69
70	```
71	draw_chart_analysis(action="create", drawing={
72	"type": "support",
73	"points": [
74	{"time": <touch_1>, "price": <level>},
75	{"time": <touch_2>, "price": <level>}
76	],
77	"options": {"text": "Scalp Level"}
78	})
79	```
80
81	### 4. Report to Orchestrator
82
83	Technique selected, timestamped quote, order type, expected fill, entry, invalidation, target, total cost estimate, capacity, and context-timeframe bias.
84
85	## Evidence and Validation
86
87	- Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
88	- Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
89	- Include spread, fees, slippage, borrow or funding, partial fills, and latency. Reject the setup when net expectancy is not positive or depends on one narrow parameter.
90	- Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
91	- Research basis: [Barber et al.](https://academic.oup.com/raps/article-pdf/10/1/61/31788119/raz006.pdf) found aggregate day-trader performance was negative and persistent profitability rare, making net-of-cost evidence and strict loss limits essential.
92
93	## Key Rules
94
95	- Exclude scheduled event windows unless a separately tested event strategy and mandate apply.
96	- Reject markets and order sizes that fail the spread, depth, fill-rate, latency, or cost gate.
97	- Exit on the predeclared invalidation; do not widen risk after entry.
98	- Enforce the mandate's session loss and order-rate limits; pause on feed, clock, or execution anomalies.
99	- Compare context-aligned and context-agnostic variants rather than assuming alignment adds edge.
100	- Do not deploy from win rate alone; require positive net expectancy and stable tail losses.
101
102	## Related Skills
103
104	- range-trading -- range scalping is a micro-timeframe application of range principles
105	- momentum-trading -- momentum scalping borrows directional confirmation logic

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scalping-strategy

15stars2forks

View on GitHub

How to install scalping-strategy?

ske-labs/agent-trading-skills/scalping-strategy

$npx -y skills add SKE-Labs/agent-trading-skills --skill scalping-strategy

Installs into the current project.

Summary

Evaluate and plan very short-horizon trades in highly liquid markets. Use when the user needs an executable scalp with latency, spread, fee, slippage, and capacity controls.

Files · 1

View on GitHub

SKILL.md

1	# Scalping Strategy
2
3	Target small, frequent profits from minimal price movements on 1m-5m timeframes.
4
5	## Setup Conditions
6
7	\| Factor \| Requirement \|
8	\| --- \| --- \|
9	\| Data \| Timestamped quotes/trades plus closed bars \|
10	\| Cost gate \| Expected gross edge exceeds spread, fees, slippage, and adverse selection \|
11	\| Liquidity \| Tested depth, order size, fill rate, and cancellation behavior \|
12	\| Risk \| Hard per-trade and session loss limits from the portfolio mandate \|
13	\| Deployment \| Positive held-out expectancy in the intended venue and session \|
14
15	## Scalping Techniques
16
17	### 1. Momentum Scalping
18
19	Enter on strong momentum candles on 1m, ride for small gain, exit immediately on momentum loss.
20
21	```
22	get_indicators(indicator_code="rsi", symbol=<symbol>, exchange=<exchange>, interval="1m")
23	get_indicators(indicator_code="macd", symbol=<symbol>, exchange=<exchange>, interval="1m")
24	```
25
26	Define an objective closed-bar momentum trigger and exit. RSI/MACD are correlated price transforms; retain them only if they improve held-out net results over a price-only baseline.
27
28	### 2. Level Scalping
29
30	Quick bounces at key S/R levels with tight stops.
31
32	```
33	get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval="5m", date=<date>)
34	```
35
36	Identify levels on the context timeframe, define a numerical rejection on the execution timeframe, and place invalidation beyond the level plus expected stop slippage. Require the planned payoff to remain positive after costs.
37
38	### 3. Range Scalping
39
40	Buy support, sell resistance within a defined micro-range. Repeat until range breaks.
41
42	```
43	get_indicators(indicator_code="dmi", symbol=<symbol>, exchange=<exchange>, interval="5m")
44	```
45
46	Use a calibrated range classifier; ADX alone does not confirm a micro-range. Stop applying the rule when the closed-bar invalidation or liquidity gate fails.
47
48	## Workflow
49
50	### 1. Confirm Direction on 5m
51
52	```
53	get_indicators(indicator_code="ema", symbol=<symbol>, exchange=<exchange>, interval="5m")
54	get_indicators(indicator_code="dmi", symbol=<symbol>, exchange=<exchange>, interval="5m")
55	```
56
57	Establish bias from higher timeframe before scalping on 1m.
58
59	### 2. Identify Setup on 1m
60
61	```
62	get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval="1m", date=<date>)
63	get_indicators(indicator_code="rsi", symbol=<symbol>, exchange=<exchange>, interval="1m")
64	```
65
66	Pick one technique (momentum, level, or range) based on current conditions.
67
68	### 3. Mark Key Levels
69
70	```
71	draw_chart_analysis(action="create", drawing={
72	"type": "support",
73	"points": [
74	{"time": <touch_1>, "price": <level>},
75	{"time": <touch_2>, "price": <level>}
76	],
77	"options": {"text": "Scalp Level"}
78	})
79	```
80
81	### 4. Report to Orchestrator
82
83	Technique selected, timestamped quote, order type, expected fill, entry, invalidation, target, total cost estimate, capacity, and context-timeframe bias.
84
85	## Evidence and Validation
86
87	- Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
88	- Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
89	- Include spread, fees, slippage, borrow or funding, partial fills, and latency. Reject the setup when net expectancy is not positive or depends on one narrow parameter.
90	- Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
91	- Research basis: [Barber et al.](https://academic.oup.com/raps/article-pdf/10/1/61/31788119/raz006.pdf) found aggregate day-trader performance was negative and persistent profitability rare, making net-of-cost evidence and strict loss limits essential.
92
93	## Key Rules
94
95	- Exclude scheduled event windows unless a separately tested event strategy and mandate apply.
96	- Reject markets and order sizes that fail the spread, depth, fill-rate, latency, or cost gate.
97	- Exit on the predeclared invalidation; do not widen risk after entry.
98	- Enforce the mandate's session loss and order-rate limits; pause on feed, clock, or execution anomalies.
99	- Compare context-aligned and context-agnostic variants rather than assuming alignment adds edge.
100	- Do not deploy from win rate alone; require positive net expectancy and stable tail losses.
101
102	## Related Skills
103
104	- range-trading -- range scalping is a micro-timeframe application of range principles
105	- momentum-trading -- momentum scalping borrows directional confirmation logic

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6 picks

Type