Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add dvgamerr-app/gokub-mcp --skill playbookgit clone --depth 1 https://github.com/dvgamerr-app/gokub-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dvgamerr-app/gokub-mcp/playbook)<a href="https://agentmods.dev/skills/dvgamerr-app/gokub-mcp/playbook"><img src="https://agentmods.dev/badge/skills/dvgamerr-app/gokub-mcp/playbook/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dvgamerr-app/gokub-mcp/playbook"><img src="https://agentmods.dev/badge/skills/dvgamerr-app/gokub-mcp/playbook.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00097 | $0.02106 |
| Opus 5 | $0.00048 | $0.01053 |
| Sonnet 5 | $0.00019 | $0.00421 |
| Haiku 4.5 | $0.00010 | $0.00211 |
Grade A, and why
playbook scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bitkub Trade Playbook
Long-only swing trading on Bitkub THB pairs via the gokub-mcp tools. The tools are the hands; this is the brain. Follow the flow, respect the guardrails, never skip the validation gate.
Execution discipline (never violate)
- Run the full flow autonomously. Never pause mid-flow to ask whether to continue. Screen → regime → signal → size → validate → decide — all in one pass.
- Report results, not options. End with a decision table (pass/fail per coin, with entry/stop/TP for any that pass) and the reason. Never end with "ถ้าต้องการจะรันต่อ…" or any conditional offer.
- No raw data dumps. Never return raw candle arrays or large result blobs to the user. Summarize each intermediate step in ≤ 1 line.
Hard guardrails (never violate)
- Risk ≤ 2% of equity per trade. Size from the stop, not from a fixed amount.
- Long only, uptrend only. No shorting, no counter-trend entries.
- No entry unless
validate_trade_setupreturnscan_trade=true. This is the gate. - Take-profit ≥ 2R. If R:R < 2, skip the trade.
- Bitkub has NO native stop/OCO. Protect positions with
client_side_stop_worker(poll it on a loop untiltriggered=true). Never assume a resting stop exists. - Never lower a trailing stop. Move it up only.
- No averaging down on a short-term plan.
Key mechanic: indicators need candles
The analysis tools (check_market_regime, calculate_atr, calculate_rsi,
detect_breakout_signal, detect_pullback_signal, calculate_ema, calculate_roc)
take arrays (prices or OHLCV candles), not a symbol. So always:
get_historical_candles(symbols=[symbol], format="close")— returnsresult.prices[]directly.- Pass
result.pricesinto price-based tools (EMA, RSI, ROC, regime) or useresult.candles(default format) for OHLCV tools (ATR, breakout, pullback, exit signals).
Use the big timeframe (1D / 240) for regime + relative strength, the entry timeframe (60 / 15) for ATR + entry signals.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 132 lines · 97 tokens per session scan A 865366e96263
playbook is a skill published in the GitHub repository dvgamerr-app/gokub-mcp (2 stars, last pushed 24d ago), licensed MIT. It adds 97 tokens to every session and 2,106 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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