Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Developer Tools
tradr
Onchain trade execution engine. Feed a CA + score, get full trade lifecycle — sized entry, mode-based exits, on-chain verification, and trade logging. Requires Bankr skill.
skill openclawclawhub Free
Onchain trade execution engine. Feed a CA + score, get full trade lifecycle — sized entry, mode-based exits, on-chain verification, and trade logging. Requires Bankr skill.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, adapters/README.md, adapters/example-adapter.py, config-template.json, dashboard/index.html, scripts/exit-manager.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
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- Download the package from Yavira.
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- Paste one of the prompts below and point your agent at the extracted folder.
New install
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- riskanon
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Documentation
tradr
Full onchain trade execution engine. You bring the signal, tradr handles everything else. Input: Contract address + score Output: Buy → monitor → exit (mechanical) No signal generation. No opinion on what to buy. All opinion on how to manage it once you're in.
Quick Start
# 1. Install ./scripts/setup.sh # 2. Edit config vi config.json # Add wallet addresses, tune scoring/modes # 3. Start the exit manager daemon sudo systemctl start tradr-exit-manager # 4. Feed a trade python3 scripts/tradr-enter.py <CA> --score <N> [--chain base] [--mode snipe]
Prerequisites
OpenClaw running (the agent runtime) Bankr skill installed (~/.openclaw/skills/bankr/) with a valid API key — this is what executes on-chain trades. Sign up at bankr.bot to get your API key, then add it to ~/.openclaw/skills/bankr/config.json Python 3.8+ and jq A funded wallet (Solana and/or EVM) — Bankr creates wallets for you on supported chains (Base, Solana, ETH, Polygon, Unichain). Fund them before trading.
Step-by-Step
Install tradr: cd ~/.openclaw/skills/tradr # or wherever you unpacked the skill ./scripts/setup.sh # creates config, installs systemd service Configure your wallets: Edit config.json and add your wallet addresses under wallets. These are used for on-chain balance verification (read-only — tradr never touches your private keys). Tune your strategy: score_to_size — how much USD to spend at each confidence level modes — exit behavior profiles (stop loss, take profit, trailing stop) mcap_ceiling_usd — maximum market cap for entries Start the exit manager: sudo systemctl start tradr-exit-manager sudo systemctl status tradr-exit-manager # verify it's running Connect a signal source: tradr doesn't generate signals — you bring your own. See adapters/README.md for the interface spec and adapters/example-adapter.py for a working template. Or feed trades manually: python3 scripts/tradr-enter.py 0xABC... --score 5 --chain base --token PEPE Monitor via dashboard: The dashboard/index.html file provides a real-time dashboard. It expects four API endpoints: GET /api/positions — returns positions.json contents GET /api/trades — returns trade-log.jsonl as JSON array GET /api/tradr-config — returns config.json contents GET /api/health — returns system health (optional) You can serve these from any HTTP server that reads the flat files, or embed the dashboard in your existing server.
File Layout
tradr/ ├── config.json # Your live config (created from template) ├── config-template.json # Default config for new installs ├── SKILL.md # This file ├── scripts/ │ ├── tradr-enter.py # Entry engine │ ├── exit-manager.py # Exit daemon │ ├── setup.sh # Installer │ └── notify-telegram.sh # Example notification hook ├── adapters/ │ ├── README.md # Signal adapter interface spec │ └── example-adapter.py # Working adapter template └── dashboard/ └── index.html # Real-time monitoring dashboard
Signal Adapters
tradr is execution-only — it doesn't have opinions about what to buy. You bring the signal, tradr handles the trade lifecycle. The interface is one command: python3 scripts/tradr-enter.py <ca> --score <N> [--chain <chain>] [--token <name>] A signal adapter is any script or service that watches a source, detects signals, scores them, and calls that command. See adapters/README.md for the full spec and adapters/example-adapter.py for a working template. Signal source ideas: Twitter KOL tracking, on-chain whale monitoring, Telegram alpha groups, DEX volume spikes, copy-trading apps, custom aggregators.
Scripts
scripts/tradr-enter.py — Entry engine. Takes CA + score, sizes position, buys via Bankr, writes position with mode attached. scripts/exit-manager.py — Exit daemon. Polls prices, applies mode-specific exit rules, sells via Bankr, verifies on-chain, logs everything. Runs as systemd service. scripts/setup.sh — Installer. Creates config from template, sets up systemd service.
Exit Modes
Each position carries a mode that determines its exit behavior. Four built-in modes ship as defaults — you can customize them or create your own. ModeStop AtTake ProfitTrailingUse Casesnipe0.85x1.3x (sell 30%)10% from peakQuick in/out. Low-conviction plays.swing0.70x1.3x (sell 30%)Tiered: 15% tight / 25% wideStandard hold. The default.gamble0.50xnone30% from peakHigh risk, let it ride or die.diamondnonenonenonePure conviction. Manual exit only. Swing mode has tiered trailing: tight trail (15%) when peak is below 2x, wide trail (25%) when peak is above 2x. Protects modest gains while letting big winners run.
Custom Modes
Add your own modes by adding a key to modes in config.json. Any name works — the exit manager reads mode params dynamically. No code changes needed. "modes": { "snipe": { ... }, "swing": { ... }, "my-custom-mode": { "stop_at": 0.80, "take_profit_1": 1.2, "take_profit_1_size": 0.5, "trailing_stop": 0.12 } } Then use it: tradr-enter.py <CA> --score 5 --mode my-custom-mode
Mode Selection
Modes are selected per-trade in order of priority: Explicit --mode flag on entry (always wins) Score-based auto-selection via score_to_mode config map default_mode fallback (default: swing)
Entry Guards
tradr rejects entries that fail any of these checks: **Mcap ceiling -- token mcap exceeds mcap_ceiling_usd default: $10M) Cooldown — same token was closed less than cooldown_minutes ago (default: 30) Max position size — scored size exceeds max_position_size_usd Already in position — open position exists for this CA
Partial Sell Tracking
When a take-profit triggers, tradr tracks remaining_usd on the position. This means: P&L calculations account for what was already sold at TP vs what's left at final exit The trade log records actual sold amounts, not the full original position You can see how much USD value is still in play at any time
Notification Hook
The notification script receives three arguments: level, type, message. level: info, trade, warning, error type: buy, sell, confluence, error, info message: human-readable text This lets your hook route notifications — e.g., buys to DM only, sells to DM + broadcast channel. Example hook: #!/bin/bash LEVEL="$1" TYPE="$2" MSG="$3" if [ "$TYPE" = "sell" ]; then # Route to both DM and broadcast send-dm "$MSG" send-broadcast "$MSG" else # Everything else just DM send-dm "$MSG" fi
Config Reference
config.json (created from config-template.json on first setup): positions_file — path to positions.json trade_log — path to trade-log.jsonl log_file — path to tradr.log bankr_script — path to bankr.sh lockfile — exit manager lock (prevents duplicates) poll_interval_seconds — price check interval (default: 10) dexscreener_delay — delay between DexScreener calls (default: 1.5s) reconcile_every_cycles — on-chain reconciliation interval (default: every 30 cycles) modes — exit params per mode (add custom modes here) stop_at — exit multiplier (e.g. 0.85 = sell if price drops to 0.85x entry) take_profit_1 — first TP multiplier (null = no TP) take_profit_1_size — fraction to sell at TP (e.g. 0.3 = 30%) trailing_stop — trail % from peak (null = no trail) trailing_stop_tight — optional tight trail (swing mode) trailing_stop_tight_below — peak threshold for tight vs wide default_mode — fallback mode when not specified score_to_mode — map of score thresholds → mode names score_to_size — map of score thresholds → position size in USD mcap_ceiling_usd — reject entries above this mcap (0 = no limit) cooldown_minutes — block re-entry on same token for N minutes after close (0 = no cooldown) max_position_size_usd — hard cap on any single position wallets.solana — Solana wallet address (for on-chain verification) wallets.evm — EVM wallet address (for on-chain verification) rpc_urls — custom RPC endpoints per chain notifications.enabled — enable/disable notifications notifications.script — path to notification hook script (receives: level, type, message)
Dashboard
tradr ships with a real-time monitoring dashboard (dashboard/index.html) that shows: Open positions — live P&L, entry/current/peak market cap, exit mode, time held Performance stats — total P&L, win rate, avg peak, best trade Trade history — searchable table with entry/exit details, tx links Configuration — collapsible view of exit modes, sizing tiers, limits The dashboard is a standalone HTML file that fetches data from four JSON API endpoints. It auto-refreshes every 15 seconds. Dark theme, mobile responsive. To use it, serve these endpoints from your HTTP server: GET /api/positions — contents of positions.json GET /api/trades — trade-log.jsonl parsed as { "trades": [...] } GET /api/tradr-config — contents of config.json GET /api/health — system health (optional)
Architecture
Signal Source (your adapter) | | CA + score [+ chain] [+ token] v tradr-enter.py | |-- Guards: mcap ceiling, cooldown, size cap |-- Resolves mode (explicit > score_to_mode > default) |-- Sizes position (score_to_size map) |-- Fetches price/mcap from DexScreener |-- Executes buy via bankr.sh |-- Writes positions.json (with mode + remaining_usd fields) |-- Logs to trade-log.jsonl |-- Notifies (type=buy) | v exit-manager.py (daemon, 10s poll) | |-- Reads positions.json |-- For each open position: | |-- Reads position's mode → gets exit params from config | |-- Fetches price from DexScreener | |-- Applies: hard stop → TP → trailing | |-- Executes sell via bankr.sh if triggered | |-- Tracks remaining_usd after partial sells | |-- Verifies on-chain balance (Solana RPC / EVM eth_call) | |-- Updates positions.json + trade-log.jsonl | |-- Notifies (type=sell) | |-- Every N cycles: reconcile (close stale positions where wallet is empty)
Position Schema
Each position in positions.json (keyed by contract address): { "token": "EXAMPLE", "chain": "base", "buy_ts": "2026-02-11T14:00:00Z", "entry_mcap": 500000, "entry_price": 0.0001, "buy_amount_usd": 7.50, "remaining_usd": 7.50, "mode": "swing", "score": 5, "current_mcap": 600000, "current_price": 0.00012, "peak_mcap": 700000, "first_exit_done": false, "closed": false, "close_ts": null, "close_reason": null, "close_mcap": null, "close_multiple": null, "est_pnl_usd": null, "tx_hash": "0x..." }
Requirements
Python 3.8+ Bankr skill installed (~/.openclaw/skills/bankr/) jq (used by bankr.sh) systemd (for exit manager daemon) No paid APIs. No LLM cost. Pure Python.
What tradr Is Not
Not a signal generator. It doesn't tell you what to buy. You bring the alpha. Not an LLM. Zero AI cost at runtime. Pure Python, pure math. Not a wallet. It never holds or accesses private keys. Execution goes through Bankr. Not opinionated about chains. Works on Solana, Base, Ethereum, Polygon, Unichain — anywhere Bankr supports.
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs2 Scripts1 Config1 Files
- SKILL.md
- adapters/README.md
- adapters/example-adapter.py
- scripts/exit-manager.py
- config-template.json
- dashboard/index.html