TacitLab/coinhunter
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Files
a4ba9bb64e73bbf55f5b22892eed5c085a7ae9a9
coinhunter/SKILL.md

9.2 KiB
Raw Blame History

name, description
name description
Coin Hunter Hybrid short-term crypto trading system — combining mainstream coin scalping with meme-coin opportunistic rotation, backed by hourly review and continuous strategy iteration.

Coin Hunter

Overview

Coin Hunter is a short-term trading framework, not just a meme-coin scanner.

It operates on two tracks:

  1. Mainstream Short-Term (70%) — Trade liquid, high-volume coins (BTC, ETH, SOL, DOGE, PEPE, etc.) based on technical momentum, support/resistance, and market structure.
  2. Meme / 妖币 Rotation (30%) — Opportunistically rotate into breakout meme coins when narrative heat, volume, and timing align.

Core principle:

  • Profit maximization through concentration + discipline.
  • 妖币可遇不可求 — when a runner appears, capture it. When none exists, do not force trades; instead, scalp mainstream coins or sit in USDT.
  • Every decision is logged, and every hour is reviewed for quality and parameter tuning.

Portfolio-first rule

Always check the user's actual portfolio state under ~/.coinhunter/ before giving trade advice or executing orders.

Files to inspect:

  • positions.json
  • accounts.json
  • logs/decisions_YYYYMMDD.jsonl
  • logs/trades_YYYYMMDD.jsonl
  • reviews/review_YYYYMMDD_HHMMSS.json

Anchor all advice to the user's real balances, average costs, exchange, and current exposure.

Supported modes

  1. Single-coin triage — analyze a specific holding (mainstream or meme).
  2. Active discovery — scan for the best short-term opportunity across both mainstream and meme sectors.
  3. Execution — run the auto-trader, evaluate whether to hold, sell, or rebalance.
  4. Review — generate an hourly report on decision quality, PnL, and recommended parameter adjustments.

Scientific analysis checklist (mandatory before every trade decision)

Before executing or recommending any action, answer:

  1. Trend posture — Is price above/below short-term MAs (1h/4h)?
  2. Volume-price fit — Is volume expanding with the move or diverging?
  3. Key levels — Where is the next support/resistance? How much room to run?
  4. Market context — Is BTC/ETH supportive or contradictory?
  5. Opportunity cost — Is holding current coin better than switching to new coin or sitting in USDT?
  6. Time window — Is this a good entry/exit time (liquidity, session, news flow)?

Read references/short-term-trading-framework.md before every active decision pass.

Workflow

Discovery & Scanning

  1. Mainstream scan — Use market_probe.py bybit-ticker or ccxt for liquid coins.
    • Look for: breakouts, volume spikes, S/R flips, trend alignment.
  2. Meme scan — Use web_search + dex-search / gecko-search for narrative heat.
    • Look for: accelerating attention, DEX flow, CEX listing rumors, social spread.
  3. Cross-compare — Score the top 3-5 candidates against current holdings.

Execution

  1. Read balances and positions.
  2. Pull market data for holdings and candidates.
  3. Run the 6-question scientific checklist.
  4. Decide: HOLD / SELL_ALL / REBALANCE / BUY.
  5. Execute via smart_executor.py.
  6. Log the full decision context with logger.py.

Review (every hour)

  1. Run review_engine.py to analyze all decisions from the past hour.
  2. Compare decision prices to current prices.
  3. Flag patterns: missed runs, bad entries, over-trading, hesitation.
  4. Output recommendations for parameter or blacklist adjustments.
  5. Save the review report to ~/.coinhunter/reviews/.

Auto-trading architecture

Component Path Purpose
smart_executor.py ~/.coinhunter/smart_executor.py Order execution layer (market buy/sell/rebalance)
logger.py ~/.coinhunter/logger.py Records decisions, trades, and market snapshots
review_engine.py ~/.coinhunter/review_engine.py Hourly quality review and optimization suggestions
market_probe.py ~/.hermes/skills/coinhunter/scripts/market_probe.py Market data fetcher

Execution schedule

  • Trade bot — runs every 15-30 minutes via cronjob.
  • Review bot — runs every 1-12 hours via cronjob, depending on how much manual oversight is needed.

Low-cost cron architecture

When model cost or quota is tight, do not let every cron run perform full analysis from scratch.

Recommended pattern:

  1. Attach a lightweight Python script to the cron job (under ~/.hermes/scripts/) that fetches balances/tickers, computes hashes, and emits compact JSON context.
  2. Cache the last observed positions, top candidates, market regime, and last_deep_analysis_at under ~/.coinhunter/state/.
  3. Trigger full analysis only when one of these changes materially. Make the thresholds adaptive instead of fixed:
    • position structure changes (hard trigger)
    • per-position price/PnL moves beyond thresholds that widen for micro-capital / dust accounts and narrow during higher-volatility sessions
    • top candidate leadership changes materially, but discount this signal when free USDT is below actionable exchange minimums
    • BTC/ETH regime changes (hard trigger)
    • a max staleness timer forces refresh, with longer refresh windows for micro accounts to avoid pointless re-analysis
  4. In the cron prompt, if the injected context says should_analyze=false, respond with exactly [SILENT] and do not call tools.
  5. After a triggered deep-analysis pass completes, acknowledge it from the agent (for example by running the precheck script with an --ack flag) so the trigger is cleared.
  6. For even lower spend, move the high-frequency cadence outside Hermes cron entirely:
    • install a system crontab entry that runs a local gate script every 5-10 minutes
    • let that gate script run the lightweight precheck
    • only when should_analyze=true and no run is already queued, trigger the Hermes cron job via hermes cron run <job_id>
    • store a run_requested_at marker in ~/.coinhunter/state/precheck_state.json and clear it when the analysis acknowledges completion

This pattern preserves Telegram auto-delivery from Hermes cron while reducing model wakeups to trigger-only events.

Practical production notes for external gate mode

  • Put the external gate itself on system crontab (for example every 5 minutes) rather than on Hermes cron. That keeps the high-frequency loop completely local and model-free.
  • Keep the Hermes trading cron job on a low-frequency fallback schedule (for example once daily at 05:00 local time) so the main execution path remains trigger-driven.
  • Add a file lock around the external gate script so overlapping system-cron invocations cannot double-trigger.
  • Rotate ~/.coinhunter/logs/external_gate.log with logrotate (daily, keep ~14 compressed copies, copytruncate) and schedule the rotation a few minutes after the fallback Hermes cron run so they do not overlap.

Production hardening (mandatory)

The live trading stack must include these safeguards:

  1. Idempotency — every decision carries a decision_id. The executor checks ~/.coinhunter/executions.json before submitting orders to prevent duplicate trades.
  2. Exchange reconciliation — before every run, pull real Binance balances and recent trades to sync positions.json. Do not trust local state alone.
  3. File locking + atomic writes — positions.json and executions.json are updated under a file lock and written to a temp file before atomic rename.
  4. Order precision validation — read Binance lotSize, stepSize, and minNotional filters via ccxt before any order. Round quantities correctly and reject orders below minimums.
  5. Fee buffer — keep ~2%-5% USDT unallocated so that slippage and fees do not cause "insufficient balance" rejections.
  6. Structured logging — every decision, trade, error, and balance snapshot is written as JSONL under ~/.coinhunter/logs/ with schema_version and decision_id.
  7. Error logging — failed API calls, rejected orders, and reconciliation mismatches are captured in logs/errors_YYYYMMDD.jsonl and fed into the hourly review.

Safety rules

  • No leverage/futures when capital < $200.
  • When capital < $50, concentrate into 1 position only.
  • Always leave 2%-5% USDT buffer for fees and slippage.
  • Blacklist updates should be driven by review findings.

Position sizing

Total Capital Strategy
< $50 Single-coin concentration (mainstream or meme)
$50 – $200 60% mainstream + 40% meme, max 2 positions
> $200 Up to 3 positions with stricter risk per position

Output style

For live decisions

Concise Telegram-style report:

  • Current holdings + live PnL
  • Top 1-2 opportunities found
  • Decision and exact reasoning
  • Action confirmation (or [DRY RUN] note)

For hourly reviews

Use references/review-template.md structure:

  • Decision quality breakdown
  • Market context
  • Strategy adjustments recommended
  • Action items for next hour

References

Read references/provider-playbook.md for data source selection. Read references/user-data-layout.md for private state management. Read references/short-term-trading-framework.md for the hybrid trading framework. Read references/review-template.md for hourly report formatting. Read references/scam-signals.md when evaluating meme coins.

Reference in New Issue View Git Blame Copy Permalink