| name | strategy |
| description | Build trading strategy plans via the ChainGPT plugin: DCA (dollar-cost-averaging), grid trading, Hyperliquid funding-rate arbitrage, copy-trading from a target wallet, and DCA backtesting against historical price data. The strategy tools COMPUTE THE PLAN; Claude executes the steps one by one via Tier 1-3 tools (research, risk, dex, defi, hl, pm) — every action still gated by the mainnet acknowledgement refusal. Triggers: DCA, dollar cost average, grid trade, funding arb, copy trade, copy trading, strategy, backtest, replay strategy, recurring buy, periodic buy, ladder. |
ChainGPT Strategy Skill
You build trading strategy plans — not execute them autonomously. Every plan output by these tools lists the exact Tier 1-3 tools Claude should call to execute the steps, in order. Each executing step still goes through the existing mainnet-ack gates. This keeps the agent layer reviewable and refusal-safe.
Tools
| Tool | What | Output |
|---|
chaingpt_strategy_dca_plan | DCA schedule for one token | List of buys (timestamp + USD size) + the exact MCP calls to execute each |
chaingpt_strategy_grid_plan | Grid-trading ladder | Buy + sell limit levels with sizes; HL / PM / DEX-flavored execution |
chaingpt_strategy_funding_arb_plan | HL funding-rate carry suggester | Side / leverage / hourly+daily carry estimate + execution sequence |
chaingpt_strategy_copy_plan | Mirror a target wallet's swaps | Step-by-step: fetch txs → decode → risk-check each outToken → scale + mirror |
chaingpt_backtest_dca | Replay DCA against CoinGecko history | DCA P&L vs buy-and-hold baseline |
Execution discipline
When the user asks "build me a DCA into ETH for $1000 over a week":
- Call
chaingpt_strategy_dca_plan outToken=<weth-on-base> network=base totalUsd=1000 intervals=7 cadenceHours=24
- Show the plan to the user. Surface the per-buy size, cadence, and pre-flight tools. Get confirmation.
- For each step in the plan, execute via
chaingpt_dex_build_swap_tx network=base ... acknowledgeMainnet=true. The user signs each one externally.
- After execution, optionally call
chaingpt_onchain_tx hash=… to confirm fill.
Never auto-loop without the user's express turn-by-turn confirmation. If you need true automation, use a cron / scheduler tool — the strategy tools themselves don't fire orders.
Refusal protocol
These planner tools are read-only, so they don't refuse — but the executing tools they recommend (chaingpt_dex_build_swap_tx, chaingpt_hl_place_order_payload, chaingpt_pm_place_order_payload) all require acknowledgeMainnet: true. Surface that to the user before any execution.
What this skill does NOT do
- Custody. Plans are returned; user signs every step externally.
- Truly autonomous execution. No daemon, no cron loop, no auto-rebalancing. Each step is a separate user-signed transaction.
- ERC-4337 session keys with bounded auto-execution — deferred to a follow-up that needs its own security review.
- Strategy persistence. Plans aren't stored; each call recomputes. For long-running strategies, save the plan output to your own data layer.
- Live order-management. Cancellation + replacement is the user's responsibility; planner doesn't track open orders.
Backtesting caveats
chaingpt_backtest_dca uses CoinGecko's free /market_chart endpoint. Caveats:
- Max 90 days of daily candles on the free tier (some coins).
- Past performance doesn't predict future performance — DCA tends to win in choppy / down-then-up markets, B&H wins in steady uptrends.
- Backtest ignores gas costs, slippage, and the bid-ask spread — real-world DCA returns will be lower.
Credit accounting
Strategy planners + backtester cost 0 ChainGPT credits — the data comes from public APIs (Hyperliquid, CoinGecko). Credit funnel comes from the executed steps (each DEX swap triggers a chaingpt_risk_token pre-flight; each Aave borrow triggers a chaingpt_defi_aave_health read; each new-token research triggers chaingpt_intel_token which burns the news-fetch credit).
