kill-zones

Name: kill-zones
Author: SKE-Labs

15stars2forks

How to install kill-zones?

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

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

Installs into the current project.

Summary

Analyze intraday session seasonality and test time-window filters. Use when timing a strategy around exchange, London, New York, or Asian trading sessions with correct timezone and daylight-saving handling.

Files · 1

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SKILL.md

1	# Kill Zones Trading
2
3	Named session windows used by ICT-style traders. Activity, volatility, spreads, and returns vary intraday, but the best window is instrument-, venue-, season-, and strategy-specific.
4
5	## Session Schedule
6
7	\| Session \| Reference window \| Required handling \|
8	\| ---------- \| --------------- \| ------------------------------------ \|
9	\| Asian \| Relevant exchange/local session \| Exchange holidays and product hours \|
10	\| London \| Europe/London local time \| Convert with historical/current DST \|
11	\| New York \| America/New_York local time \| Convert with historical/current DST \|
12
13	Define candidate window boundaries in local session time, then convert every timestamp with a timezone database. Do not publish fixed UTC windows across DST changes.
14
15	## Session Behaviors
16
17	For each instrument, measure time-of-day median volume, spread, realized volatility, jump frequency, and the strategy's net returns. Treat prior-session ranges and sweeps as hypotheses; sessions do not create a mandatory daily direction.
18
19	## Workflow
20
21	1. Pre-session: Mark Asian session high/low, identify HTF key levels, note scheduled news events
22	```
23	get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval="15m", date=<asian_session_date>)
24	```
25	2. Session open: measure spread, volatility, and any predeclared sweep; do not label price discovery manipulation
26	3. Entry timing: apply the strategy's calibrated window and closed-bar trigger
27	4. Session context:
28	- Record which prior-session levels were crossed and whether price closed back inside
29	- Estimate subsequent-return distributions without imposing bullish/bearish labels
30
31	## Evidence and Validation
32
33	- Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
34	- Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
35	- 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.
36	- Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
37	- Research basis: [Ito & Hashimoto](https://www.nber.org/papers/w12413) documents intraday seasonality in FX activity, volatility, and spreads; it does not establish universal profitable windows or a mandatory direction.
38
39	## Key Rules
40
41	- Do not call opening moves manipulation without order-level evidence.
42	- Allow trades outside named windows when the validated strategy and liquidity gates pass.
43	- Never assume London or another session is most profitable; show instrument-specific held-out results.
44	- Include DST, holidays, half-days, venue hours, and scheduled announcements.
45	- Treat time-window and structural labels as features whose incremental value must be tested.
46
47	## Related Skills
48
49	- liquidity-zones — Kill zone opens frequently sweep Asian session liquidity before reversing
50	- market-structure-shift — test objective structure events inside the chosen session window

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kill-zones

15stars2forks

View on GitHub

How to install kill-zones?

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

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

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Kill Zones Trading
2
3	Named session windows used by ICT-style traders. Activity, volatility, spreads, and returns vary intraday, but the best window is instrument-, venue-, season-, and strategy-specific.
4
5	## Session Schedule
6
7	\| Session \| Reference window \| Required handling \|
8	\| ---------- \| --------------- \| ------------------------------------ \|
9	\| Asian \| Relevant exchange/local session \| Exchange holidays and product hours \|
10	\| London \| Europe/London local time \| Convert with historical/current DST \|
11	\| New York \| America/New_York local time \| Convert with historical/current DST \|
12
13	Define candidate window boundaries in local session time, then convert every timestamp with a timezone database. Do not publish fixed UTC windows across DST changes.
14
15	## Session Behaviors
16
17	For each instrument, measure time-of-day median volume, spread, realized volatility, jump frequency, and the strategy's net returns. Treat prior-session ranges and sweeps as hypotheses; sessions do not create a mandatory daily direction.
18
19	## Workflow
20
21	1. Pre-session: Mark Asian session high/low, identify HTF key levels, note scheduled news events
22	```
23	get_candles_around_date(symbol=<symbol>, exchange=<exchange>, interval="15m", date=<asian_session_date>)
24	```
25	2. Session open: measure spread, volatility, and any predeclared sweep; do not label price discovery manipulation
26	3. Entry timing: apply the strategy's calibrated window and closed-bar trigger
27	4. Session context:
28	- Record which prior-session levels were crossed and whether price closed back inside
29	- Estimate subsequent-return distributions without imposing bullish/bearish labels
30
31	## Evidence and Validation
32
33	- Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
34	- Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
35	- 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.
36	- Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
37	- Research basis: [Ito & Hashimoto](https://www.nber.org/papers/w12413) documents intraday seasonality in FX activity, volatility, and spreads; it does not establish universal profitable windows or a mandatory direction.
38
39	## Key Rules
40
41	- Do not call opening moves manipulation without order-level evidence.
42	- Allow trades outside named windows when the validated strategy and liquidity gates pass.
43	- Never assume London or another session is most profitable; show instrument-specific held-out results.
44	- Include DST, holidays, half-days, venue hours, and scheduled announcements.
45	- Treat time-window and structural labels as features whose incremental value must be tested.
46
47	## Related Skills
48
49	- liquidity-zones — Kill zone opens frequently sweep Asian session liquidity before reversing
50	- market-structure-shift — test objective structure events inside the chosen session window

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6 picks

Type