liquidity-zones

Name: liquidity-zones
Author: SKE-Labs

15stars2forks

How to install liquidity-zones?

ske-labs/agent-trading-skills/liquidity-zones

$npx -y skills add SKE-Labs/agent-trading-skills --skill liquidity-zones

Installs into the current project.

Summary

Mark candidate liquidity levels and test sweep/reversal behavior. Use when analyzing equal highs/lows, swing levels, round-number clustering, or stop-loss cascade risk without inferring hidden intent.

Files · 1

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SKILL.md

1	# Liquidity Zones Trading
2
3	Observable price levels where stop or limit orders may cluster. Clustering can contribute to cascades, but candles alone cannot identify the orders, their owners, institutional targeting, or a guaranteed reversal.
4
5	## Identification
6
7	### Buy-Side Liquidity (BSL)
8	- Location: Above swing highs, equal highs, resistance
9	- Hypothesis: Some buy stops may rest above the level; verify with available order/trade data
10
11	### Sell-Side Liquidity (SSL)
12	- Location: Below swing lows, equal lows, support
13	- Hypothesis: Some sell stops may rest below the level; verify with available order/trade data
14
15	### Level Features
16
17	Record formation type, number of touches, equality tolerance in ATR/ticks, age, visible depth if available, distance, and time of day. Calibrate these features rather than assigning ordinal strength.
18
19	## Workflow
20
21	1. Identify liquidity pool (equal highs/lows, obvious swing points):
22	```
23	get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval=<interval>, date=<date>)
24	```
25	2. Mark levels using `draw_chart_analysis`: `resistance` for BSL, `support` for SSL, `highlight` for sweep points
26	3. Wait for sweep — price takes out the level
27	4. Confirm reversal: use an objective swing/rejection rule and a predeclared return window
28	5. Enter after confirmation
29	6. Stop loss beyond the sweep wick
30	7. Target opposite liquidity pool
31
32	## Evidence and Validation
33
34	- Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
35	- Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
36	- 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.
37	- Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
38	- Research basis: [Osler](https://www.newyorkfed.org/research/staff_reports/sr150.html) found clustered FX stop-loss orders can contribute to price cascades. This supports conditional liquidity hypotheses, not certainty that institutions target a visible level.
39
40	## Key Rules
41
42	- Define sweep distance, close condition, reversal window, and expiry before evaluation.
43	- Compare anticipation, reversal, and continuation hypotheses on identical samples.
44	- Use time-of-day relative volume; it is contextual, not proof of stop orders.
45	- Equal highs/lows are candidate clustering coordinates, not known liquidity or magnets.
46	- Return `no trade` when the level or trigger cannot be defined without hindsight.
47
48	## Related Skills
49
50	- kill-zones — Liquidity sweeps most commonly occur during London and NY AM sessions
51	- market-structure-shift — CHoCH after a sweep confirms the reversal direction

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liquidity-zones

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View on GitHub

How to install liquidity-zones?

ske-labs/agent-trading-skills/liquidity-zones

$npx -y skills add SKE-Labs/agent-trading-skills --skill liquidity-zones

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Liquidity Zones Trading
2
3	Observable price levels where stop or limit orders may cluster. Clustering can contribute to cascades, but candles alone cannot identify the orders, their owners, institutional targeting, or a guaranteed reversal.
4
5	## Identification
6
7	### Buy-Side Liquidity (BSL)
8	- Location: Above swing highs, equal highs, resistance
9	- Hypothesis: Some buy stops may rest above the level; verify with available order/trade data
10
11	### Sell-Side Liquidity (SSL)
12	- Location: Below swing lows, equal lows, support
13	- Hypothesis: Some sell stops may rest below the level; verify with available order/trade data
14
15	### Level Features
16
17	Record formation type, number of touches, equality tolerance in ATR/ticks, age, visible depth if available, distance, and time of day. Calibrate these features rather than assigning ordinal strength.
18
19	## Workflow
20
21	1. Identify liquidity pool (equal highs/lows, obvious swing points):
22	```
23	get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval=<interval>, date=<date>)
24	```
25	2. Mark levels using `draw_chart_analysis`: `resistance` for BSL, `support` for SSL, `highlight` for sweep points
26	3. Wait for sweep — price takes out the level
27	4. Confirm reversal: use an objective swing/rejection rule and a predeclared return window
28	5. Enter after confirmation
29	6. Stop loss beyond the sweep wick
30	7. Target opposite liquidity pool
31
32	## Evidence and Validation
33
34	- Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
35	- Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
36	- 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.
37	- Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
38	- Research basis: [Osler](https://www.newyorkfed.org/research/staff_reports/sr150.html) found clustered FX stop-loss orders can contribute to price cascades. This supports conditional liquidity hypotheses, not certainty that institutions target a visible level.
39
40	## Key Rules
41
42	- Define sweep distance, close condition, reversal window, and expiry before evaluation.
43	- Compare anticipation, reversal, and continuation hypotheses on identical samples.
44	- Use time-of-day relative volume; it is contextual, not proof of stop orders.
45	- Equal highs/lows are candidate clustering coordinates, not known liquidity or magnets.
46	- Return `no trade` when the level or trigger cannot be defined without hindsight.
47
48	## Related Skills
49
50	- kill-zones — Liquidity sweeps most commonly occur during London and NY AM sessions
51	- market-structure-shift — CHoCH after a sweep confirms the reversal direction

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6 picks

Type