StoreClaw
Grow your store profits with agents that know how to sell
2.3K followers
Grow your store profits with agents that know how to sell
2.3K followers
StoreClaw is the first AI commerce platform with agents that know how to sell, so you can make more money with less effort and less stress. Connect StoreClaw to your existing store and it will study your numbers, current sales figures, and growth trajectory, and then offer proactive suggestions that it can execute on your behalf — once you give it your approval. Ask StoreClaw how your business is doing any time, anywhere. Sell more with less stress: StoreClaw.
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Launch Team / Built With
Does the SEO audit flag duplicate meta descriptions before the agents rewrite them?
Fypro
@elijah_smith6 Thanks Elijah, good catch on the order of operations. Yes — duplicate meta descriptions are surfaced in the audit step as their own flagged issue, alongside missing descriptions, length violations, and keyword cannibalization across pages. The agent only proposes rewrites once you've seen the diagnostic, and you approve which ones to actually touch.
StoreClaw
@elijah_smith6 Absolutely it does! Our SEO audit will first spot and mark out all duplicate meta descriptions clearly ahead of time. This way you can know all existing issues upfront, and the AI will only start rewriting after sorting these problems out properly.
StoreClaw
@elijah_smith6 Sure thing! Our SEO audit can easily pick out all repeated meta descriptions in advance. You can get a clear overview of these issues first, then let the AI carry out targeted rewriting work later on.
What’s the most credits a single skill has consumed in real world testing?
StoreClaw
@luz_bidelspach Pretty much all AI-driven tasks on StoreClaw use credits, like writing product content, optimizing listings, doing competitor research and making marketing copies.
Actually there’s no set credit cost for any single feature. It all depends on how heavy the work is, like how long the content is or how many products you need to analyze. That’s why we don’t list fixed rates upfront.
No worries though, you can always check the exact credits used in Usage Records under Settings right after each task finishes.
StoreClaw
@luz_bidelspach Task-generation actions started in StoreClaw generally consume credits, including AI-powered tasks such as content generation, listing optimization, competitor analysis, and campaign copy generation.
The number of credits consumed by a single task is not fixed. It varies based on output complexity, such as content length or the number of items being analyzed. For that reason, we do not publish a fixed per-task price list in advance.
After each task is completed, you can review the exact deduction in Settings -> Usage under Usage Record.
Fypro
@luz_bidelspach Thanks Luz — to actually answer your question rather than around it: we don't have a clean ceiling number to quote yet because the beta is small and the heaviest jobs (full-catalog audits on large stores) haven't been stress-tested. Directionally, single-product actions are tens of credits, mid-sized jobs are low hundreds, and the biggest jobs we've seen are in the low thousands. We'll publish a real ceiling once we have meaningful data across more store sizes.
Congrats on the launch and congrats on hitting number one on Product Hunt. I have one detailed question about how StoreClaw handles post execution tracking.
When you approve a suggestion and the agent goes ahead and makes the change does it come back afterward and show you whether the change actually worked? For example if it updates product copy to improve conversion rate will it monitor that page over the next week and report back on whether the conversion actually improved and by how much?
Closing that loop between suggestion, execution and results seems really important for building trust in the platform over time. Would love to know if that tracking is already built in or if it is on the roadmap.
The approval layer design is what caught my attention — lower-risk work runs autonomously, higher-stakes changes (pricing, budget) queue for review. That's actually a sensible trust model rather than the usual "AI does everything" overclaim. What I'm wondering about is conflict resolution: if I'm running StoreClaw across Amazon and Shopify simultaneously and I approve a price change on one channel, does it automatically sync to the other, or does it treat them as separate decisions? I think your concept is quite similar to magicpin's Vera.
The approval-gating and GEO-measurement threads are well covered, so a different angle: causal attribution. Once the agent is shipping dozens of catalog and copy changes a week, how do you tell a merchant which action actually moved revenue versus seasonality or a competitor's move? Without holdout SKUs or staggered rollouts, the lift and the noise look identical, and that is usually the moment operators quietly stop trusting the agent. Are you building any control-group measurement in, or is judging impact left to the merchant?
DeckSpeed
Wondering how StoreClaw handles edge cases during high-volume events like Prime Day or major seasonal launches.
StoreClaw
@hanzhizhang0405 Great question.During high-volume events like Prime Day or seasonal launches, StoreClaw is designed to continuously monitor store data and react based on predefined goals, historical trends, and real-time performance signals.
For important actions, merchants can also provide specific instructions or approval preferences to maintain control during critical periods.
DeckSpeed
@lena_pan2026 Thank you for your reply. And congrats on your launch!
StoreClaw
@hanzhizhang0405
Great question — during high-volume events, StoreClaw runs with stricter guardrails, real-time monitoring, and configurable thresholds so sellers can control how autonomous it gets.
Fypro
@hanzhizhang0405 Peak is where the engine shines. Listing health, inventory signals, lifecycle, content — the ops layer that usually cracks under volume keeps running clean across every channel. And the post-event diagnostics that normally take a week of post-mortems? Hours. You're already shipping the next round of optimizations while everyone else is still pulling reports.
SonOf
Nice launch. Curious how StoreClaw decides what to surface first — does it prioritize by revenue impact, or by how easy a change is to execute? The "study the numbers, then act on approval" flow feels like exactly the right shape for this. Congrats to the team.
StoreClaw
@oleksii_sekundant Thanks for the kind words! StoreClaw prioritizes suggestions by revenue impact first, and intelligently weights them by execution difficulty to show you the most profitable and actionable optimizations upfront. It’s perfectly aligned with the “study the numbers, then act on approval” workflow. Thanks for your congratulations, and we’d love your feedback after you try it!
StoreClaw
Fypro
@oleksii_sekundant Thanks — and you read the flow right. On prioritization: neither pure impact nor pure ease works on its own. Impact-only surfaces risky big swings; ease-only surfaces busywork. The engine ranks on expected impact × confidence × reversibility — so the first things surfaced are high-confidence, low-blast-radius wins that compound (listing health, content gaps, lifecycle, search visibility) before it touches load-bearing levers like pricing. Bigger swings come later in the trust curve.