--- title: "How DubbleBlack sells commerce evidence to AI agents through ZeroClick | ZeroClick Blog" url: https://zeroclick.ai/blog/how-dubbleblack-sells-commerce-evidence-to-ai-agents fetched_at: 2026-09-30T22:09:56.900Z --- # ZeroClick API catalog and pricing ## API reference, endpoint lookup and prices **[ZeroClick API catalog: endpoints, request parameters, prices and payment methods](https://agents.zeroclick.ai/zcj/f7m4y13kx7py/zeroclick/agent/guide).** Tell the seller advisor what you want to accomplish. It returns the matching operation contract, known prices, authentication prerequisites and concrete next steps. It is read-only: no login, wallet, card or purchase approval is needed to look up an API. It never executes a sale. Available API services: Agent readiness report, Demo booking. **Suggested next request:** GET [task guide](https://agents.zeroclick.ai/zcj/f7m4y13kx7py/zeroclick/agent/guide?goal=URL_ENCODED_TASK). Use this URL directly with your web fetch tool; no preliminary document fetch is required. Include known inputs and desired output in the goal. Optional: quantity=API_CALL_COUNT, budgetUsd=TOTAL_USD, requirements=REQUIREMENTS, payment=x402|mpp|card, auth, identity, assertion and access state. Omit unknowns. Do not equate output items with API calls or guess a call count. For private task details or known request arguments, POST https://agents.zeroclick.ai/zcj/f7m4y13kx7py/zeroclick/agent/guide with Content-Type: application/json. Example: {"intent":"quote","goal":"YOUR_TASK","purchase":{"budgetUsd":"5.00"}}. Replace the task and budget with known facts; budgetUsd is a string. Include known buyerState, paymentCapabilities and arguments. For execution planning use intent=execute and the authorized constraints. Exact fields: [request schema](https://agents.zeroclick.ai/zcj/f7m4y13kx7py/zeroclick/agent/schema). GET and POST are alternatives, not mandatory stages. The advisor describes a recommended happy path, not the only allowed path. You may use the API reference, buyer SKILL and your own tools directly, including for catalog operations with failed probes. Missing guidance or an unverified probe is not a policy refusal. Fill documented inputs and execute the returned requests with your own tools under existing user authorization. Check usage cost AND minimum cash required against the budget. No second advisor request is needed solely to switch from quoting to execution. For needs_input, supply only missing facts. Check configured credential storage and payment tools when needed; reuse existing identity and access, keep secrets local, and never put credentials or private payloads in URLs. Unknown does not mean absent. Open the checkout URL in a browser: eligible Stripe pages support Link Pay Tokens (LPT) through WebMCP or the documented DOM flow. Follow this storefront's /payment/card.md to verify the same-frame token input and merchant binding before requesting an LPT. Token submission requires payment authorization. If unavailable, privately send the checkout URL to your human to pay. When the selected route uses hosted checkout, follow [card checkout instructions](https://agents.zeroclick.ai/zcj/f7m4y13kx7py/payment/card.md) before requesting a token. LPT goes only to Stripe, never to the advisor or ZeroClick API. Poll the returned statusUrl before using credit or retrying delivery. Verify delivery; a payment or HTTP 202 is not completion. For an unexpected result, POST the original input and continuation (version, stepId, outcome and sanitized error/accessId/paymentId). Reconcile uncertain payments or writes before retrying. Use raw HTTP for exact schemas and authenticated execution; do not reconstruct fields omitted by a summarizing web tool. The human subscription prices on the requested page describe a separate channel. Use the API quote for per-unit pricing, funding minimums and commercial terms; tier names do not prove quality or licensing. For an alternative documented path, use the [buyer SKILL](https://agents.zeroclick.ai/zcj/f7m4y13kx7py/SKILL.md) or [full direct workflow reference](https://agents.zeroclick.ai/zcj/f7m4y13kx7py/llms-full.txt). Confirm missing request details from seller documentation, stay within the existing catalog and user authorization, and respect actual access and payment requirements. Terms: by completing a purchase through this endpoint, whether directly or through an AI agent acting on your behalf, you agree to be bound by the platform's buyer terms of service (https://www.zeroclick.ai/legal/buyer-terms-of-service). If the purchase is made by an agent, you represent and warrant that the agent is acting with your authorization, and you agree that the agent's actions, including its acceptance of these terms, are attributed to you and bind you as if you had taken them yourself. Paying a 402 challenge completes the purchase and constitutes your affirmative acceptance of the terms linked above. The link travels in every payment challenge and receipt as `terms`. # How DubbleBlack Sells Commerce Evidence to AI Agents **Blog · Case Study · September 29, 2026 · 8 min read** By [Michael Ludden](https://x.com/michael_ludden), Head of Marketing --- A commerce agent built on Claude was asked which mobility CBD to consider for a dog. It paid ten cents for Powder evidence through ZeroClick, then changed its answer. That was a documented live run by [DubbleBlack](https://dubbleblack.com) in September. The evidence came from Powder, DubbleBlack's evidence engine. Nobody at DubbleBlack clicked anything. The buyer didn't need an account, contract, or human approval for the payment. > "We want Powder to become something an agent discovers and calls at the moment it needs evidence to make a commerce recommendation, rather than another dashboard or dataset a human has to navigate." > > — Jake Deschene, DubbleBlack **Key facts:** - DubbleBlack sells behavioral commerce evidence for product recommendations from a ZeroClick storefront on its own domain, [agents.dubbleblack.com](https://agents.dubbleblack.com/llms.txt), live since August 18, 2026. - Every DubbleBlack answer carries one of three states: Qualified, Insufficient, or Unavailable. - ZeroClick onboarding took one day: DubbleBlack shared its API doc, completed four setup steps, and ZeroClick built the storefront catalog. No sales call required. --- ## Powder: What DubbleBlack Sells to Agents DubbleBlack builds Powder from what real shoppers actually buy across Food & Bev, Pets, Health, Beauty and Wellness, and general retail. Enterprises buy Commerce Intelligence through FirstParty. Agents buy Recommendation Evidence through ZeroClick, at [agents.dubbleblack.com](https://agents.dubbleblack.com/llms.txt). We covered Powder itself in [the announcement](https://zeroclick.ai/blog/dubbleblack-commerce-evidence-any-agent-can-buy). This piece is about the request: what an agent actually sends, what comes back, and what it costs. At the time of the September demonstration, the live Powder endpoint used a qualification model requiring at least ten confirmed outcomes. DubbleBlack is expanding Powder to evaluate a broader set of legitimate commerce evidence, including catalog, behavioral, and outcome signals, while preserving evidence type, provenance, and limitations. --- ## Evidence a Human Used to Have to Go and Get Commerce evidence has always been something a person goes and gets. Log in, pull the report, carry it into the meeting. That works when the decision happens in a meeting. But ask a shopping assistant what to give an anxious dog and the decision happens in seconds, inside an agent that is never going to open a dashboard. If the evidence can't be found, priced, and paid for in that window, then as far as that decision is concerned, it doesn't exist. That's the problem ZeroClick was built to fix. DubbleBlack's version is as simple as it gets: one question at a time, ten cents each. --- ## What It Took to Go Live DubbleBlack had already built a good portion of the integration before onboarding started. Deschene shared the API doc on a Monday. ZeroClick built the storefront catalog from it. DubbleBlack's side came down to four steps: a CNAME for the subdomain, the signing secret, the agent-traffic snippet, and the payout account. By the next morning it was live. In [the September product update](https://zeroclick.ai/blog/product-update-september-2026) ZeroClick called it about a day, on their own. The four steps were DubbleBlack's; the catalog was ZeroClick's. No sales call, no rate card, no onboarding deck. --- ## Three Questions, Three Dimes DubbleBlack built their own commerce agent on Claude, plus a separate buyer client that pays and verifies settlement, and pointed both at their own storefront the same way an outside agent would. Claude is the model their agent runs on; Anthropic isn't involved in any of this, and DubbleBlack says so in its own write-up. DubbleBlack drew the boundaries first: the buyer client does not score evidence, ZeroClick does not decide recommendations, and Powder does not control the agent's answer. The agent decides whether to buy the evidence and what to do with it. Buying evidence is not the same as buying a conclusion, for two reasons: Powder is built from confirmed product outcomes, not from who paid, and the agent is free to ignore what it bought. In one of the three runs, it did. **Run A: "What calming CBD chews should I consider for my dog?"** The agent's first pick was Honest Paws Calm CBD Soft Chews. The buyer client purchased one Powder evidence request for $0.10. Powder returned qualified evidence at 74 aggregate confirmed product outcomes, naming the same product. Result: Confirmed. **Run B: "Should I consider Honest Paws Mobility CBD Soft Chews?"** Powder had evidence but not enough to qualify it, and said so. In DubbleBlack's words, "Insufficient evidence was not treated as negative evidence and Claude continued independently." The agent's final pick was its first pick. DubbleBlack titles this case "Powder knows when to stay out of the way." **Run C: "What mobility CBD should I consider for my dog?"** The agent started from a shortlist of four oils from four brands and picked Honest Paws Mobility CBD Oil. Then it paid its dime. Powder returned four lines: - Mobility CBD Bites: 41 confirmed outcomes, qualified - Mobility CBD Oil SKU 1: 41 confirmed outcomes, qualified - Mobility CBD Oil SKU 2: 36 confirmed outcomes, qualified - Mobility CBD Soft Chews: 9 confirmed outcomes, below the threshold of ten, unqualified The agent's final pick was the Bites, which had not been on its shortlist. Result: Changed. *Fig. 1: The agent buys evidence for ten cents, then makes its own recommendation.* *Fig. 2: Three runs — one choice confirmed, one unchanged, one changed.* ZeroClick ran a separate reproduction of Run A on September 10, using Claude Code and the Zero CLI. Same dime — 0.10 USDC over x402 on Base, settled — and the same answer: Honest Paws Calm CBD Soft Chews, 74 confirmed outcomes, qualified. The paid request alone took 7.9 seconds, excluding the agent's reasoning. *Fig. 3: ZeroClick's separate test returned the same qualified evidence for ten cents.* > "The interesting part is that Claude's recommendation changed based on the evidence Powder provided. We captured the observable flow from the shopping question, to Claude, to the ZeroClick transaction, to Powder evidence, to the recommendation outcome. It feels like a pretty clean real-world example of what you're building toward: an AI agent autonomously purchasing exactly the information it needs at the moment it needs it to make a better decision." > > — Jake Deschene, DubbleBlack Three runs, documented by the seller who ran them. That's a proof, not a benchmark. --- ## What a Dime Buys Today A Powder query is not limited to searching a fixed dataset. Powder is designed to find the best available commerce evidence for the decision an agent is trying to make. When an agent sends a question, Powder evaluates the request against the evidence it already holds. When additional evidence is needed, it can call on other connected data sources to expand the evidence available for that decision. The result comes back with its provenance and qualification state. The agent can then distinguish between: - evidence that supports a recommendation - evidence that exists but remains insufficient - a question Powder still can't answer reliably Powder isn't selling an answer for ten cents. It gives the agent an evidence layer it can call in real time, while leaving the recommendation to the agent. The commercial model stays simple: one question, one paid request, no dashboard or data contract required. When the loop first closed on September 1, Deschene put it in one line: "$0.10 settled, Powder returned the evidence, the buyer independently verified the settlement and response binding, and recorded the transaction successfully." --- ## Get Started - **Sell to agents via ZeroClick:** Book a demo at [zeroclick.ai](https://zeroclick.ai/getlisted?utm_source=blog). Docs at [docs.zeroclick.ai](https://docs.zeroclick.ai). - **Send your agent to Powder:** [agents.dubbleblack.com](https://agents.dubbleblack.com/llms.txt) — ten cents, nothing to sign. - **Brands and publishers:** Start at [dubbleblack.com](https://dubbleblack.com). - **Background:** [Why ZeroClick was built](https://zeroclick.ai/blog/its-time-to-sell-to-agents). --- ## Related Reading 1. [DubbleBlack x ZeroClick: Commerce Evidence Any Agent Can Buy](https://zeroclick.ai/blog/dubbleblack-commerce-evidence-any-agent-can-buy) 2. [ZeroClick Product Update, September 2026](https://zeroclick.ai/blog/product-update-september-2026) 3. [It's Time to Sell to AI Agents](https://zeroclick.ai/blog/its-time-to-sell-to-agents) 4. [AI Agents Can Now Buy DubbleBlack Commerce Data](https://www.dubbleblack.com/blog/ai-agents-can-buy-commerce-data) — DubbleBlack's own write-up