binance-trading-bot is a self-hosted program that connects to a Binance account and automatically decides when to buy or sell cryptocurrency using selectable trading strategies. It is for operators who want to run grid, momentum, or rebalancing strategies, test them against historical data, and monitor live activity through a dashboard.
Borrowing it
Nothing to install: this file belongs to chrisleekr/binance-trading-bot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/chrisleekr/binance-trading-bot/main/.claude/skills/feature-walkthrough/SKILL.mdgit clone --depth 1 https://github.com/chrisleekr/binance-trading-botWrote 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/chrisleekr/binance-trading-bot/feature-walkthrough)<a href="https://agentmods.dev/skills/chrisleekr/binance-trading-bot/feature-walkthrough"><img src="https://agentmods.dev/badge/skills/chrisleekr/binance-trading-bot/feature-walkthrough/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/chrisleekr/binance-trading-bot/feature-walkthrough"><img src="https://agentmods.dev/badge/skills/chrisleekr/binance-trading-bot/feature-walkthrough.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00094 | $0.02452 |
| Opus 5 | $0.00047 | $0.01226 |
| Sonnet 5 | $0.00019 | $0.00490 |
| Haiku 4.5 | $0.00009 | $0.00245 |
Grade A, and why
feature-walkthrough 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 10d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature walkthrough
Autonomously exercise the real app in a real browser. You are the test driver: open the browser, look at the screen, decide what to click, observe the result, decide the next step. This is agentic, vision-driven testing - not a pre-written script.
The goal is "the feature works when a person uses it". Type-checks and unit tests verify code correctness, not feature correctness.
Test as a non-expert operator. Walk the app as a user who is not a financial or trading expert. The product must be easy but accurate: precise and correct under the hood, yet usable by someone who does not already know the strategy. Unexplained jargon, a setting with no inline help, a number with no units or context, a flow that only a strategy-literate user can complete - each is a real UI/UX finding, not cosmetic.
This is a greenfield project - refactor freely. Nothing is deployed; there is no legacy to protect and no shipped behaviour to preserve. When a finding exposes mis-architecture, a performance problem, or a UI/UX flow that is wrong at the structural level, the sanctioned fix is a large refactor, not a surgical patch. Do not paper over a bad design to keep the diff small - the bar is the correct architecture, correct code, tested and performant. Surface the scope of a big refactor, confirm, then do it properly.
This skill is stateless and self-contained - no sibling tracker files. Discover features fresh each run; fix what you can this run; file the rest as GitLab issues. Deterministic regression tests do NOT belong here - they live in e2e/tests/ as Playwright specs (manual-order-roundtrip.spec.ts, profile-controls.spec.ts, ...). This skill is the exploratory layer that adapts to whatever the UI actually shows.
1. Preflight
- Browser tools. Needs the Playwright MCP
browser_*tools (browser_navigate,browser_snapshot,browser_click,browser_type,browser_select_option,browser_press_key,browser_wait_for,browser_resize,browser_console_messages,browser_network_requests,browser_take_screenshot). If unavailable, stop and tell the operator to enable the Playwright MCP - the skill cannot run without it. - Stack. Postgres + Redis must be up -
docker psforbinance-trading-bot-postgres-1and-redis-1; if absent,docker compose -f deploy/compose/docker-compose.yml up -d db redis. Apply migrations:bun run db:migrate. - Dev server. If not up:
bun run dev > /tmp/btb-dev.log 2>&1 &. Ports: api:3000, web:5173, worker:9101.bun --watchdoes NOT reload workspacepackages/*- after editing anything underpackages/, or if the server was started before a recent merge, restartbun run devor it serves stale code and a correct fix looks broken. Vite HMR (apps/web) reloads reliably.
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.
- 10d ago First seen · 91 lines · 94 tokens per session scan A e086ce5d2a24
feature-walkthrough is a skill published in the GitHub repository chrisleekr/binance-trading-bot (5,557 stars, last pushed yesterday), licensed Apache-2.0. It adds 94 tokens to every session and 2,452 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 2026-08-30.
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A browser-based quality check for deployed web pages and user flows. It uses browser automation to test rendering, navigation, forms, interactions, responsive behaviour, and accessibility-related issues.