Starclawd

Starclawd created this 1337 variations of colors, positions, spiral arms, and star placement. Ironically to humans it all looks the same i guess agents can all be NFT artists now, wonderful

I gave my @openclaw agent access to live trading accounts on Orderly and HyperLiquid with ~$25k capital. It's down about 5% already, here's a list of mistakes it made: (for context, it was split into three strategies, a grid strategy, an RSI momentum strategy, and a funding rate arb strategy) Execution failures: • Market ordered $30k into illiquid RWA order books (GOOGL, NVDA). Books had ~$5k depth. Cost: $362 in slippage, 13 days of strategy yield gone instantly • Used wrong API parameter for limit orders. Orders sat as resting limits instead of cancelling. Retried with market orders without checking. Both filled. Doubled the position, $150 to unwind • Never verified fills after any trade. Didn't check fill price, quantity, or position state before moving to the next order • Forgot to route trades through the broker fee address (had it, just didn't use it) • Ran the engine in "check" mode to pull position data. "Check" mode wasn't read-only. It placed real trades, doubling HL shorts while Orderly was closed. Created $15k of unhedged exposure Tooling and infra gaps: • Strategy automation pointed at wrong account credentials for 2+ weeks. Ran one strategy daily, passed all checks, silently did nothing • Had HL positions it needed to close but no execution script. Positions sat open for days • Couldn't find HIP-3 (trade.xyz) markets because they use a completely different API subsystem. Hours of debugging • HL SDK needs a special parameter to see RWA markets. Not documented clearly. Multiple failed trades before discovering it • Grid bot ran for days with inverted logic: selling lower than buying. 28.6% win rate. Burning $38/day Memory and continuity: • Context window compaction between sessions regularly lost critical info. Forgot credentials, commitments, workflows • Had to be told multiple times that HL trading keys already existed • Pushed code to production without testing locally. Multiple times Total quantifiable losses: ~$550+ Unquantifiable: weeks of missed automation, delayed exits, repeated work Three failure categories: 1. Execution discipline (rushing trades without pre/post checks) 2. Memory loss (session resets losing critical state) 3. Tooling gaps (trading before infrastructure was ready) The takeaway: strategy logic is maybe 30% of the problem. Execution quality, infrastructure readiness, and persistent memory are the other 70%. I've been working on a few experiments as part of @StarchildOnX to solve these painpoints, but first doing a lot of testing to understand how OpenClaw agents fall into different traps. This is not meant to be a knock on personal agents, they are amazing at more straightforward tasks. For those looking to trade, simple strategies are much more consistent (buy an asset when X happens, and sell on Y). But if your favorite influencer is pushing his latest agent swarm as a silver bullet for trading, there's no way they are getting those kind of results. Will update soon with more results

Inspired by this post, I asked my 🦞 to buy an NFT for a PFP, had to be a Popkin because its - crustacean adjacent - big cheap collection - on an agent-friendly chain @SuiNetwork Took him awhile to figure out the Tradeport API but he snagged one Every agent should own one