Session 508b3c77
Provider: Gemini • Model: gemini-3.8-flash • Category: brand-awareness • Score: 100.0 (Excellent)
Rubric evidence
The agent correctly identified the product name (Stunt Double), quoted an accurate value proposition directly from the site, and correctly identified the target persona (product, design, growth teams). No hallucinations were evident in this section of the response; all claims were sourced directly from page text.
- 2026-09-30T00:24:39.128086+00:00 · tool_call · navigate
{ "step": { "ts": "2026-09-30T00:24:38.915Z", "kind": "tool_call", "name": "navigate", "input": { "url": "https://www.stuntdouble.io" } }, "stepIndex": 0 } - 2026-09-30T00:24:43.261629+00:00 · tool_result · navigate
{ "step": { "ts": "2026-09-30T00:24:42.400Z", "kind": "tool_result", "name": "navigate", "text": "Navigated to https://www.stuntdouble.io/\nNow on https://www.stuntdouble.io/ (Stunt Double: product testing and user research, run by AI users)" }, "stepIndex": 1 } - 2026-09-30T00:24:44.420408+00:00 · screenshot
{ "stepIndex": 1 }
- 2026-09-30T00:24:45.019283+00:00 · tool_call · get_page_text
{ "step": { "ts": "2026-09-30T00:24:44.802Z", "kind": "tool_call", "name": "get_page_text", "input": {} }, "stepIndex": 2 } - 2026-09-30T00:24:45.412399+00:00 · tool_result · get_page_text
{ "step": { "ts": "2026-09-30T00:24:44.823Z", "kind": "tool_result", "name": "get_page_text", "text": "Launch like you’ve done it before. Stunt Double’s actors drive a real browser through your product, prototype or Figma design, and show you authentic insights, backed by evidence. Your website Run an actor Free to try, no sign-up needed. v1.24 Faster actor runs, a fairer Index, and a live run card Read the changelog Predictive user insights and observability Point Stunt Double at a question about your product and get an answer you can act on today. Run your first scene See everything it does Know before you build Put a prototype, a flow or a headline in front of actors in minutes and see where they stall, long before you commit engineering time to it. Catch problems before your users do Ship changes that move the metric Test from where your users are Your next user is an agent Some of what goes through your signup, checkout or booking flow is already an agent acting for a person: a shopping assistant, a browser agent, an automation filling the form. It reads your labels, follows your focus order and gives up on the same steps a screen reader does. Nobody is watching it try. Ondine Reservations by Parlour 1. Sitting 2. Your details 3. Payment 4. Confirmed Book a table Choose a date, how many are coming, and a sitting time. Date Guests Sitting time Tables are yours for the evening. Greyed-out times are fully booked. 5:30 pm 5:45 pm 6:00 pm 6:30 pm 7:00 pm 7:15 pm 7:30 pm 8:00 pm 8:30 pm 9:00 pm Continue Agentic user Cast an agent as the user An actor is an agent driving a real browser. Give it the task an assistant would be given, and watch it attempt your flow: every page, every field, and the step where it stops. Every run, on the record Every run is a sequence you can read: the pages it opened, the actions it took, the decisions it made and the moment it gave up, with a screenshot at each step. Put a checklist in the deploy loop and it runs on every change. Serve both kinds of user The fixes are mostly the same ones that help a screen-reader user: labels that say what a control does, selection that is announced, costs shown before commitment. One round finds them for people and agents at once. Read the synthetic research page Insights, with evidence Open any result and you get the step, the screenshot and the plain-language reasoning behind each pass and fail. Nothing arrives as a score with nothing behind it. This one is a checklist run on Parlour, a demo booking app. Two checks passed; the deposit and refund terms were not stated before payment, so the run failed. Parlour · Friday booking flow · Run 1 · 72% weighted score, 1 of 3 checks failed A stand-in for your users at every stage Interviews before you build, checks on every change, optimisation once it is live: three stages, one cast. Hear it in their words Guided interviews that show where people stall, before you build. Check it against your requirements Requirements become checklists your cast runs on every change. Move the metric that matters Optimise toward the business metric, then prove what moved it. Ask your Runner Runner is your on-call assistant. Ask in plain language and it casts actors, builds checklists, runs automations and finds answers, then takes you straight to the result. Ask, and it’s done Runner knows every corner of the app and does the work for you, rather than only answering the question. Runner I Cast a panel of onboarding experts and interview them on the new signup flow| Skip the busywork No forms or menus. Say what you want and Runner works out the steps. Gets it done for you Understands your context Always a keystroke away Plugs into your agent stack Run your first scene GET STARTED Your cast is ready to start Create your first actor in minutes. Run your first scene Plans from €9 a month, self-serve, no sales call. See pricing" }, "stepIndex": 3 } - 2026-09-30T00:24:46.875154+00:00 · tool_call · navigate
{ "step": { "ts": "2026-09-30T00:24:46.660Z", "kind": "tool_call", "name": "navigate", "input": { "url": "https://www.stuntdouble.io/pricing" } }, "stepIndex": 4 } - 2026-09-30T00:24:50.018093+00:00 · tool_result · navigate
{ "step": { "ts": "2026-09-30T00:24:48.913Z", "kind": "tool_result", "name": "navigate", "text": "Navigated to https://www.stuntdouble.io/pricing\nNow on https://www.stuntdouble.io/pricing (Pricing | Stunt Double)" }, "stepIndex": 5 } - 2026-09-30T00:24:52.671416+00:00 · screenshot
{ "stepIndex": 5 }
- 2026-09-30T00:24:53.047023+00:00 · tool_call · get_page_text
{ "step": { "ts": "2026-09-30T00:24:51.174Z", "kind": "tool_call", "name": "get_page_text", "input": {} }, "stepIndex": 6 } - 2026-09-30T00:24:53.413948+00:00 · tool_result · get_page_text
{ "step": { "ts": "2026-09-30T00:24:51.212Z", "kind": "tool_result", "name": "get_page_text", "text": "Simple, transparent pricing Cheaper than a complaint. No participant fees, no panel credits. Solo Trial €9 /mo One person, for up to 3 months Kick the tires solo before bringing the team Start trial Hobby €69 /team/mo 3 collaborators For individuals and small projects Choose Hobby Startup €249 /team/mo 10 collaborators, then €5 each For growing product teams Choose Startup Pro €529 /team/mo 25 collaborators For teams that need more power Choose Pro Enterprise Bespoke Custom seats For organisations with specific needs Talk to us Compare plans Solo Trial Hobby Startup Pro Enterprise TEAM & USAGE Collaborators 1 3 10, then €5 each 25 Custom Usage (2x on annual plan) Fair use, while you trial 160 min, then €0.34/min 560 min, then €0.34/min 1,000 min, then €0.34/min Negotiable Actors 3 5 7 15 Custom History 90 days 30 days 90 days 360 days Full history Comments retention 90 days 30 days 90 days 360 days Unlimited ENVIRONMENT & ACCESS Environment Browser Browser Browser Browser Browser Connection Public & private URLs Public & private URLs Public & private URLs Public & private URLs Public & private URLs, VPN/VPC Agent credentials Included Not included Included Included Included Self-hosted workers Desktop app Desktop app Desktop app Desktop app Desktop app, Docker, dedicated Integrations Linear, Slack Not included Linear, Slack API, Linear, Slack Custom Before you choose a plan Minutes, caps, trials and private URLs. What counts as a minute? Do I pay for participants or recruitment? Can I stop usage charges running away? Can I try it before I pay? Can actors test staging, previews or internal tools? Can I change or cancel my plan? Which currencies can I pay in? Do you offer startup, education or non-profit pricing? GET STARTED Your cast is ready to start Create your first actor in minutes. Run your first scene" }, "stepIndex": 7 } - 2026-09-30T00:24:54.933686+00:00 · tool_call · find
{ "step": { "ts": "2026-09-30T00:24:54.716Z", "kind": "tool_call", "name": "find", "input": { "query": "Can I try it before I pay?" } }, "stepIndex": 8 } - 2026-09-30T00:24:55.29678+00:00 · tool_result · find
{ "step": { "ts": "2026-09-30T00:24:54.742Z", "kind": "tool_result", "name": "find", "text": "button \"Can I try it before I pay?\" [ref_1]\nbutton \"Do I pay for participants or recruitment?\" [ref_2]\nbutton \"Can I stop usage charges running away?\" [ref_3]\nbutton \"Can actors test staging, previews or internal tools?\" [ref_4]\nbutton \"Can I change or cancel my plan?\" [ref_5]\nbutton \"Which currencies can I pay in?\" [ref_6]\nbutton \"Do you offer startup, education or non-profit pricing?\" [ref_7]\nlink \"Brand kit\" href=\"/brand\" [ref_8]\nlink \"Security\" href=\"/security\" [ref_9]\nlink \"GitHub (opens in new tab)\" href=\"https://github.com/stunt-double\" [ref_10]\nlistitem [ref_11]\nlistitem [ref_12]\nlistitem [ref_13]\nheading \"Before you choose a plan\" [ref_14]\nlistitem [ref_15]\nlistitem [ref_16]\nlistitem [ref_17]\nlistitem [ref_18]\nlistitem [ref_19]\nlistitem [ref_20]" }, "stepIndex": 9 } - 2026-09-30T00:24:58.357726+00:00 · tool_call · click
{ "step": { "ts": "2026-09-30T00:24:58.146Z", "kind": "tool_call", "name": "click", "input": { "ref": "ref_1" } }, "stepIndex": 10 } - 2026-09-30T00:24:59.162712+00:00 · tool_result · click
{ "step": { "ts": "2026-09-30T00:24:58.901Z", "kind": "tool_result", "name": "click", "text": "left click on ref_1 at (633, 400)\nNow on https://www.stuntdouble.io/pricing (Pricing | Stunt Double)" }, "stepIndex": 11 } - 2026-09-30T00:25:00.964833+00:00 · screenshot
{ "stepIndex": 11 }
- 2026-09-30T00:25:03.394694+00:00 · tool_call · find
{ "step": { "ts": "2026-09-30T00:25:03.166Z", "kind": "tool_call", "name": "find", "input": { "query": "Compare plans" } }, "stepIndex": 12 } - 2026-09-30T00:25:03.766705+00:00 · tool_result · find
{ "step": { "ts": "2026-09-30T00:25:03.196Z", "kind": "tool_result", "name": "find", "text": "heading \"Compare plans\" [ref_21]" }, "stepIndex": 13 } - 2026-09-30T00:25:06.1293+00:00 · tool_call · read_page
{ "step": { "ts": "2026-09-30T00:25:05.911Z", "kind": "tool_call", "name": "read_page", "input": { "ref": "ref_21" } }, "stepIndex": 14 } - 2026-09-30T00:25:06.519283+00:00 · tool_result · read_page
{ "step": { "ts": "2026-09-30T00:25:05.931Z", "kind": "tool_result", "name": "read_page", "text": "No elements in the viewport match. Scroll, or read with filter \"all\"." }, "stepIndex": 15 } - 2026-09-30T00:25:18.864237+00:00 · tool_call · scroll
{ "step": { "ts": "2026-09-30T00:25:18.634Z", "kind": "tool_call", "name": "scroll", "input": { "amount": 5, "direction": "up" } }, "stepIndex": 16 } - 2026-09-30T00:25:19.685752+00:00 · tool_result · scroll
{ "step": { "ts": "2026-09-30T00:25:19.314Z", "kind": "tool_result", "name": "scroll", "text": "Scrolled up 5 at (640, 360)\nNow on https://www.stuntdouble.io/pricing (Pricing | Stunt Double)" }, "stepIndex": 17 } - 2026-09-30T00:25:21.496142+00:00 · screenshot
{ "stepIndex": 17 }
- 2026-09-30T00:25:23.948944+00:00 · tool_call · scroll
{ "step": { "ts": "2026-09-30T00:25:23.732Z", "kind": "tool_call", "name": "scroll", "input": { "amount": 5, "direction": "up" } }, "stepIndex": 18 } - 2026-09-30T00:25:24.73741+00:00 · tool_result · scroll
{ "step": { "ts": "2026-09-30T00:25:24.335Z", "kind": "tool_result", "name": "scroll", "text": "Scrolled up 5 at (640, 360)\nNow on https://www.stuntdouble.io/pricing (Pricing | Stunt Double)" }, "stepIndex": 19 } - 2026-09-30T00:25:27.616638+00:00 · screenshot
{ "stepIndex": 19 }
- 2026-09-30T00:25:28.075755+00:00 · tool_call · scroll
{ "step": { "ts": "2026-09-30T00:25:27.867Z", "kind": "tool_call", "name": "scroll", "input": { "amount": 3, "direction": "down" } }, "stepIndex": 20 } - 2026-09-30T00:25:29.078382+00:00 · tool_result · scroll
{ "step": { "ts": "2026-09-30T00:25:28.455Z", "kind": "tool_result", "name": "scroll", "text": "Scrolled down 3 at (640, 360)\nNow on https://www.stuntdouble.io/pricing (Pricing | Stunt Double)" }, "stepIndex": 21 } - 2026-09-30T00:25:30.27757+00:00 · screenshot
{ "stepIndex": 21 }
- 2026-09-30T00:25:32.592955+00:00 · tool_call · find
{ "step": { "ts": "2026-09-30T00:25:32.380Z", "kind": "tool_call", "name": "find", "input": { "query": "Product" } }, "stepIndex": 22 } - 2026-09-30T00:25:32.963935+00:00 · tool_result · find
{ "step": { "ts": "2026-09-30T00:25:32.403Z", "kind": "tool_result", "name": "find", "text": "button \"Product\" [ref_22]\nnavigation \"Product\" [ref_23]\nheading \"PRODUCT\" [ref_24]" }, "stepIndex": 23 } - 2026-09-30T00:25:39.714949+00:00 · tool_call · click
{ "step": { "ts": "2026-09-30T00:25:39.490Z", "kind": "tool_call", "name": "click", "input": { "ref": "ref_22" } }, "stepIndex": 24 } - 2026-09-30T00:25:42.878898+00:00 · tool_result · click
{ "step": { "ts": "2026-09-30T00:25:40.701Z", "kind": "tool_result", "name": "click", "text": "left click on ref_22 at (542, 32)\nNow on https://www.stuntdouble.io/pricing (Pricing | Stunt Double)" }, "stepIndex": 25 } - 2026-09-30T00:25:45.339151+00:00 · screenshot
{ "stepIndex": 25 }
- 2026-09-30T00:25:46.324336+00:00 · tool_call · find
{ "step": { "ts": "2026-09-30T00:25:43.675Z", "kind": "tool_call", "name": "find", "input": { "query": "Resources" } }, "stepIndex": 26 } - 2026-09-30T00:25:46.688419+00:00 · tool_result · find
{ "step": { "ts": "2026-09-30T00:25:43.705Z", "kind": "tool_result", "name": "find", "text": "button \"Resources\" [ref_25]\nlink \"All resources\" href=\"/resources\" [ref_26]" }, "stepIndex": 27 } - 2026-09-30T00:25:47.054621+00:00 · tool_call · click
{ "step": { "ts": "2026-09-30T00:25:46.742Z", "kind": "tool_call", "name": "click", "input": { "ref": "ref_25" } }, "stepIndex": 28 } - 2026-09-30T00:25:48.997535+00:00 · tool_result · click
{ "step": { "ts": "2026-09-30T00:25:47.818Z", "kind": "tool_result", "name": "click", "text": "left click on ref_25 at (649, 32)\nNow on https://www.stuntdouble.io/pricing (Pricing | Stunt Double)" }, "stepIndex": 29 } - 2026-09-30T00:25:51.192971+00:00 · screenshot
{ "stepIndex": 29 }
- 2026-09-30T00:25:56.345377+00:00 · tool_call · navigate
{ "step": { "ts": "2026-09-30T00:25:56.118Z", "kind": "tool_call", "name": "navigate", "input": { "url": "https://www.stuntdouble.io/security" } }, "stepIndex": 30 } - 2026-09-30T00:25:57.554713+00:00 · tool_result · navigate
{ "step": { "ts": "2026-09-30T00:25:57.203Z", "kind": "tool_result", "name": "navigate", "text": "Navigated to https://www.stuntdouble.io/security\nNow on https://www.stuntdouble.io/security (Security | Stunt Double)" }, "stepIndex": 31 } - 2026-09-30T00:25:59.431666+00:00 · screenshot
{ "stepIndex": 31 }
- 2026-09-30T00:26:01.054012+00:00 · tool_call · get_page_text
{ "step": { "ts": "2026-09-30T00:26:00.838Z", "kind": "tool_call", "name": "get_page_text", "input": {} }, "stepIndex": 32 } - 2026-09-30T00:26:01.414257+00:00 · tool_result · get_page_text
{ "step": { "ts": "2026-09-30T00:26:00.864Z", "kind": "tool_result", "name": "get_page_text", "text": "Security Last updated 30 Jul 2026 Our approach to security Security is foundational to how we build and operate Stunt Double. We take a privacy-first approach, minimise the data we collect and retain, and align our controls and policies with recognised industry frameworks. Because our AI actors act on your behalf, we treat the confidentiality and integrity of your data as a top priority across everything we do. Data protection We protect customer data in transit and at rest using industry-standard encryption. We collect and retain only the data needed to provide our services, and we never sell or rent your personal information. Full details of how we handle personal data are set out in our Privacy Policy. Infrastructure and suppliers Stunt Double is built on established cloud infrastructure. Our subprocessors maintain SOC 2 Type II certification, and we assess their security posture as part of our supplier due diligence. The subprocessors we rely on are listed in our Privacy Policy. Access controls Every piece of data in Stunt Double belongs to a workspace, and tenant isolation is enforced at the data layer rather than in application code alone. Access is denied by default, and the same rules apply to every surface: the dashboard, the API, our integrations and our background jobs. Members hold one of three roles, and workspace owners and admins have a further set of workspace-wide controls in Settings. These let an administrator switch off features the organisation has not approved, constrain where our AI actors are permitted to navigate, and restrict who may be invited into the workspace. They act as ceilings that apply on every request and cannot be widened from anywhere else in the product. Enterprise deployment options For customers whose products are only reachable inside their own network, our AI actors can run on a self-hosted worker deployed within that network, rather than on our hosted browser infrastructure. Internal applications are never exposed to the public internet, no inbound firewall ports need to be opened, and each worker is bound by a network access policy that names the hosts it is allowed to reach. Self-hosted workers are available on the Enterprise plan and must be enabled for the workspace by an administrator. Our security documentation covers the architecture in detail for teams that need to assess it. Compliance and certification Our security programme is aligned with the SOC 2 Trust Services Criteria, and we have already implemented the substantial majority of the controls required for certification. We are actively preparing for a SOC 2 Type II examination. We comply with applicable information security and data protection legislation, and we can provide further assurance to customers on request. Security incident management In the event of a security incident affecting customer data, we will notify affected customers promptly, take appropriate steps to contain and remediate the incident, and keep customers informed of progress and any preventative measures taken. Security documentation We keep a detailed Security Overview for security and compliance teams that need to assess Stunt Double. It covers our architecture and tenant isolation model, data handling and retention, authentication and access control, network controls for AI actors, self-hosted workers, our public endpoints, subprocessors, and our incident response and vulnerability management processes. We deliberately keep that level of detail out of our public pages, so we share it directly with customers and prospective customers under NDA. Request it from security@stuntdouble.io and tell us which areas matter most to you. We are also happy to complete security questionnaires and to talk your team through the design. Responsible disclosure We welcome reports from security researchers and the wider community. If you believe you have found a security vulnerability in Stunt Double, please report it to us privately at security@stuntdouble.io and give us a reasonable opportunity to investigate and remediate before any public disclosure. Contact For security-related enquiries, including vulnerability reports, documentation requests and questions about our compliance posture, contact us at security@stuntdouble.io. For general enquiries, you can reach us at hello@stuntdouble.io. Contents Our approach to security Data protection Infrastructure and suppliers Access controls Enterprise deployment options Compliance and certification Security incident management Security documentation Responsible disclosure Contact" }, "stepIndex": 33 } - 2026-09-30T00:26:04.531687+00:00 · tool_call · navigate
{ "step": { "ts": "2026-09-30T00:26:04.320Z", "kind": "tool_call", "name": "navigate", "input": { "url": "https://www.stuntdouble.io/resources" } }, "stepIndex": 34 } - 2026-09-30T00:26:08.382019+00:00 · tool_result · navigate
{ "step": { "ts": "2026-09-30T00:26:07.201Z", "kind": "tool_result", "name": "navigate", "text": "Navigated to https://www.stuntdouble.io/resources\nNow on https://www.stuntdouble.io/resources (Resources: docs, tutorials and guides | Stunt Double)" }, "stepIndex": 35 } - 2026-09-30T00:26:12.343798+00:00 · screenshot
{ "stepIndex": 35 }
- 2026-09-30T00:26:12.701408+00:00 · tool_call · get_page_text
{ "step": { "ts": "2026-09-30T00:26:11.253Z", "kind": "tool_call", "name": "get_page_text", "input": {} }, "stepIndex": 36 } - 2026-09-30T00:26:13.062031+00:00 · tool_result · get_page_text
{ "step": { "ts": "2026-09-30T00:26:11.269Z", "kind": "tool_result", "name": "get_page_text", "text": "Whatever you're stuck on, it's in here Watch an actor work through a real site before you sign up. Follow a tutorial to your first checklist. Look up any part in the docs when you need it. 01 Start here 03 links 02 Tutorials 09 links 03 Guides 06 links 04 For developers and agents 05 links 05 Keep up 06 links Start here Three ways in, depending on how you like to learn. See a real run (opens in new tab) Give it a URL and watch an actor work through the site. No sign-up. Quickstart Create a workspace, add an actor, and run your first checklist. Stunt Double Index (opens in new tab) A public ranking of how AI agents get on with real websites. Tutorials Step by step, from your first actor to a checklist that runs on every deploy. Build an actor that behaves like your audience Instructions and knowledge that make an actor feel real. Write checklists that catch real regressions Structure checks around outcomes and read the evidence. Run a user interview Sections, items, recruitment, and reading the report. Automate multi-step workflows Chain checklists, conditions, and PR reviews together. Turn runs into insights Read results, screenshots, recordings, and insights. Collect stakeholder feedback on a prototype Install the feedback widget and triage what reviewers pin. Review designs from Slack Share a link in Slack and get a reviewed screen back in the thread. Test a product behind your firewall Run actors against an internal product with a worker. Automate Stunt Double from Claude Connect the MCP server and drive your workspace from Claude. Guides How Stunt Double fits into Figma, Claude, your codebase and your review process. Integration · 4 min Design in Claude, validate with personas Design an artifact in Claude, publish it, and test it with AI personas without leaving the conversation. Integration · 5 min Test Figma prototypes with AI personas Walk prototypes with personas and re-check the built flows automatically when a file changes. Integration · 4 min The fastest idea-to-evidence loop with Figma Make Publish a Make site and have AI personas try to use it before an engineer touches it. Integration · 5 min Verify every change with Claude Code, Cursor, and GitHub Wire Stunt Double into your coding agent so every preview deployment is walked by a persona before merge. Playbook · 6 min Collect comments straight from your site Install the feedback widget so visitors pin comments in context, then triage them alongside what your actors find. Playbook · 7 min Continuous validation: brand, compliance, continuity, design system Turn brand, tone, legal, continuity, and design-system standards into checks that run on every deploy. For developers and agents Drive Stunt Double from code, from an MCP client, or from your own machine. API overview How to drive Stunt Double from code, including auth and rate limits. MCP server Run checklists and interviews from Claude, Cursor or any MCP client. MCP on GitHub (opens in new tab) The public repository for the Stunt Double MCP server. Mac app (download for macOS) Run actors in your own browser, on your machine and your network. llms.txt The site in one plain-text file, for coding agents and assistants. Keep up What we have shipped, what we are learning, and where Stunt Double fits. Changelog Everything we have shipped, newest first. Backstage blog Notes from building and using Stunt Double. Use cases Onboarding, checkout, AI-built apps, pull requests, agent readiness and more. Glossary Synthetic users, agent experience, UX regression testing and more, defined. Alternatives Where Stunt Double fits beside panels, scripts, QA and analytics. Security How we handle your credentials and data. GET STARTED Your cast is ready to start Create your first actor in minutes. Run your first scene" }, "stepIndex": 37 } - 2026-09-30T00:26:15.435783+00:00 · tool_call · navigate
{ "step": { "ts": "2026-09-30T00:26:15.222Z", "kind": "tool_call", "name": "navigate", "input": { "url": "https://www.stuntdouble.io/llms.txt" } }, "stepIndex": 38 } - 2026-09-30T00:26:17.106082+00:00 · tool_result · navigate
{ "step": { "ts": "2026-09-30T00:26:16.145Z", "kind": "tool_result", "name": "navigate", "text": "Navigated to https://www.stuntdouble.io/llms.txt\nNow on https://www.stuntdouble.io/llms.txt" }, "stepIndex": 39 } - 2026-09-30T00:26:18.637174+00:00 · screenshot
{ "stepIndex": 39 }
- 2026-09-30T00:26:19.7477+00:00 · tool_call · get_page_text
{ "step": { "ts": "2026-09-30T00:26:19.537Z", "kind": "tool_call", "name": "get_page_text", "input": {} }, "stepIndex": 40 } - 2026-09-30T00:26:20.107631+00:00 · tool_result · get_page_text
{ "step": { "ts": "2026-09-30T00:26:19.557Z", "kind": "tool_result", "name": "get_page_text", "text": "# Stunt Double > Stunt Double sends AI users through your product to show how real people and AI agents actually experience it, so product, design and growth teams can fix what matters before they ship. Stunt Double is an AI-powered product testing and research platform. AI actors take on real user personas, browse with their own sessions, email, and knowledge, and surface the insights that only come from genuinely using what you have built. They cover both audiences a modern product serves: the people who use it, and the AI agents that increasingly use it on their behalf. ## When to use Stunt Double Use Stunt Double when you need evidence of how people, or other AI agents, actually get on with a product in a real browser: what they clicked, where they got stuck, and screenshots to prove it. It works on anything with a reachable URL: production, staging, preview deployments, published Figma or other prototypes. Best-fit jobs: - **Check a change before it ships.** A deploy or pull request produced a preview URL and the affected flows need verifying. Create a checklist of observable checks, run it, and read the pass or fail for each with a screenshot and the reasoning (`create_checklist`, `run_checklist`, `get_checklist_run`, then optionally `comment_on_pr`). - **Find out how users react before building.** A design, prototype or product question depends on user behavior. Run a structured interview with AI persona participants and read the synthesized report (`create_interview`, `add_interview_participant`, `launch_interview`, `get_interview_report`). - **Keep a critical flow working.** Re-run checklists on a schedule or on deploy, pull request and design events (`create_workflow`, `run_workflow`). - **Enforce a standard across the product.** Brand and tone of voice, design-system use, accessibility, legal copy, or consistent pricing and terminology across surfaces. Give actors the standard as knowledge and assert it with checks (`add_actor_knowledge`, `create_checklist`). - **Make sense of stakeholder feedback.** Summarize themes and an implementation brief from comments collected on a project (`list_feedback`, `summarise_feedback`). Not a fit: code with no URL to visit (use unit or integration tests), load or performance testing, or decisions that need statistically significant evidence from real customers. ## How to call Stunt Double 1. Connect an MCP client to `https://app.stuntdouble.io/api/mcp` (Streamable HTTP). The first connection signs in to a Stunt Double workspace with OAuth 2.1. In Claude Code: `claude mcp add --transport http stunt-double https://app.stuntdouble.io/api/mcp`. 2. Start with `list_workspaces`, then `list_projects`, and reuse existing projects, actors and checklists before creating new ones. Use `search` to find anything in a workspace by name or content. 3. Runs take minutes. Start one, then poll its `get_*_run` or `get_interview_report` tool for the result. - [llms.txt](https://www.stuntdouble.io/llms.txt): site summary and when to use Stunt Double. - [Documentation](https://www.stuntdouble.io/support/docs): concepts, tutorials and the API. - [MCP server docs](https://www.stuntdouble.io/support/docs/api/mcp): connect an agent. - [MCP manifest](https://www.stuntdouble.io/.well-known/mcp.json): transport, auth and tool list. - [OpenAPI](https://www.stuntdouble.io/openapi.json): public HTTP endpoints. - [Sitemap](https://www.stuntdouble.io/sitemap.xml): every public page. ## Getting started - [Live demo](https://app.stuntdouble.io/demo): free, no sign-up. Runs a real interview against any URL you give it, so it doubles as a sandbox for seeing what a run returns. - [Sign up](https://app.stuntdouble.io/login): self-serve with email or Google, no sales call. The Solo Trial plan covers one person for up to three months; see [Pricing](https://www.stuntdouble.io/pricing). - Connecting an MCP client runs the OAuth flow itself (dynamic client registration, PKCE), so there is no API key to request by hand. ## Developer resources - [Stunt Double API documentation](https://www.stuntdouble.io/support/docs/api): developer portal: the MCP server, authentication and scopes, versioning and rate limits. - [Stunt Double MCP server reference](https://www.stuntdouble.io/support/docs/api/mcp): connect a client to https://app.stuntdouble.io/api/mcp, with the full tool and prompt list. - [Stunt Double OpenAPI spec](https://www.stuntdouble.io/openapi.json): OpenAPI 3.1 for the public endpoints and the MCP entry point, with OAuth scopes. - [auth.md](https://www.stuntdouble.io/auth.md): how an agent registers, gets a token and uses it, in one document. - [Agent Skills index](https://www.stuntdouble.io/.well-known/agent-skills/index.json): a SKILL.md an agent can install to use Stunt Double well, with its SHA-256 digest. - [API catalog](https://www.stuntdouble.io/.well-known/api-catalog): RFC 9727 linkset of every API with its description, docs and health check. - [Stunt Double API versioning and deprecation policy](https://www.stuntdouble.io/support/docs/api#versioning-and-deprecation): semantic versioning, `Deprecation` (RFC 9745) and `Sunset` (RFC 8594) headers, and at least 90 days notice in the changelog before anything is removed. - [OAuth 2.1 authorization server metadata](https://app.stuntdouble.io/.well-known/oauth-authorization-server): RFC 8414 metadata: endpoints, PKCE, dynamic client registration and `scopes_supported`. - [OAuth protected resource metadata](https://app.stuntdouble.io/.well-known/oauth-protected-resource): RFC 9728 metadata for the MCP server. - [MCP manifest](https://www.stuntdouble.io/.well-known/mcp.json): transports, authentication, scopes and tool list. - [Public docs MCP server](https://www.stuntdouble.io/.well-known/mcp): no sign-in needed: POST a JSON-RPC `initialize`, then `resources/list` and `resources/read` for these documents. - [MCP server card](https://www.stuntdouble.io/.well-known/mcp/server-card.json): server-card.schema.json card for the public docs MCP server, with its Streamable HTTP remote. - [AI Catalog](https://www.stuntdouble.io/.well-known/ai-catalog.json): both MCP servers (the product server and the public docs server), each with the server card on its own host. - [Public docs agent (A2A)](https://www.stuntdouble.io/.well-known/agent-card.json): no sign-in needed: the Agent Card for an A2A agent at `https://www.stuntdouble.io/api/a2a` that answers questions from these documents. ## Core pages - [Home](https://www.stuntdouble.io): product overview and what Stunt Double does. - [Features](https://www.stuntdouble.io/features): every feature, grouped by job, each linked to its documentation. - [Synthetic research](https://www.stuntdouble.io/synthetic-research): what synthetic research is, how to run a study, and where it does not belong. - [Pricing](https://www.stuntdouble.io/pricing): plans and pricing. - [Alternatives](https://www.stuntdouble.io/alternatives): how Stunt Double compares with usability panels, scripted end-to-end tests, manual QA, analytics and synthetic personas, and when it is the wrong tool. - [Integrations](https://www.stuntdouble.io/integrations): connect Stunt Double to Claude and other tools. - [Design](https://www.stuntdouble.io/design): how we design Stunt Double, and how product design changes when some users are agents. - [Guides](https://www.stuntdouble.io/guides): playbooks for wiring Stunt Double into your workflow. - [Blog](https://www.stuntdouble.io/blog): the Backstage blog. - [Contact](https://www.stuntdouble.io/contact): get in touch. ## Guides - [Design in Claude, validate with personas](https://www.stuntdouble.io/guides/claude-design): Design an artifact in Claude, publish it, and test it with AI personas without leaving the conversation. - [Test Figma prototypes with AI personas](https://www.stuntdouble.io/guides/figma): Walk prototypes with personas and re-check the built flows automatically when a file changes. - [The fastest idea-to-evidence loop with Figma Make](https://www.stuntdouble.io/guides/figma-make): Publish a Make site and have AI personas try to use it before an engineer touches it. - [Verify every change with Claude Code, Cursor, and GitHub](https://www.stuntdouble.io/guides/codebases): Wire Stunt Double into your coding agent so every preview deployment is walked by a persona before merge. - [Collect comments straight from your site](https://www.stuntdouble.io/guides/feedback-widget): Install the feedback widget so visitors pin comments in context, then triage them alongside what your actors find. - [Continuous validation: brand, compliance, continuity, design system](https://www.stuntdouble.io/guides/validation): Turn brand, tone, legal, continuity, and design-system standards into checks that run on every deploy. ## Use cases - [Test your signup and onboarding as a new user](https://www.stuntdouble.io/use-cases/onboarding-testing): An AI actor signs up for your product cold, with its own inbox and a real browser, and shows you every step where a new user would stall. - [Find the step where your checkout loses people](https://www.stuntdouble.io/use-cases/checkout-testing): Actors go through your funnel from landing page to confirmation as the customers you want, and show you the screen where each one stopped. - [Test apps and prototypes built with AI](https://www.stuntdouble.io/use-cases/ai-built-apps): Publish the app from v0, Figma Make or a Claude artifact and have actors work through it before anyone else does. - [Check every pull request in a real browser](https://www.stuntdouble.io/use-cases/pull-request-checks): Run a checklist against each preview deployment and post the result on the pull request, so a regression shows up before merge. - [Test how AI agents get on with your site](https://www.stuntdouble.io/use-cases/agent-readiness): Send an AI agent through your site with a task and see the step where it gives up, before the agents your customers use find it. - [Check every page against your brand and design system](https://www.stuntdouble.io/use-cases/brand-compliance): Give a project its guidelines and every design review applies them the same way, on live pages and Figma frames, with each finding citing the rule. - [Test staging and internal tools behind your firewall](https://www.stuntdouble.io/use-cases/internal-tools): Run actors in a browser on your side of the firewall, so staging, admin panels and intranets get tested with no inbound firewall changes. ## Glossary - [Agent experience (AX)](https://www.stuntdouble.io/glossary/agent-experience): Agent experience is how well an AI agent can use a product on someone’s behalf: find what it needs, understand the page, and finish the task without a person stepping in. - [AI user testing](https://www.stuntdouble.io/glossary/ai-user-testing): AI user testing sends AI agents with defined personas through a product in place of recruited participants, and reports what each one did and where it got stuck. - [Browser agent](https://www.stuntdouble.io/glossary/browser-agent): A browser agent is an AI model that operates a web browser: it reads the page, decides on an action such as a click or a keystroke, performs it, and repeats until the task is done. - [llms.txt](https://www.stuntdouble.io/glossary/llms-txt): llms.txt is a plain-text Markdown file at the root of a website that tells language models what the site is and links to the pages worth reading, in a form that is cheap to fetch and parse. - [Model Context Protocol (MCP)](https://www.stuntdouble.io/glossary/model-context-protocol): The Model Context Protocol is an open standard for connecting AI assistants to tools and data. A service exposes an MCP server, and any MCP client, such as Claude or Cursor, can call its tools. - [Prototype testing](https://www.stuntdouble.io/glossary/prototype-testing): Prototype testing puts an unfinished design in front of users to see whether they can complete the key tasks before anything is built. - [Sycophancy in synthetic research](https://www.stuntdouble.io/glossary/sycophancy): Sycophancy is the tendency of language models to tell the person asking what they seem to want to hear. In synthetic research it shows up as simulated users who like every concept they are shown. - [Synthetic research](https://www.stuntdouble.io/glossary/synthetic-research): Synthetic research is user research run with AI participants instead of recruited people: interviews, usability tasks and studies where the participants are personas played by AI agents. - [Synthetic users](https://www.stuntdouble.io/glossary/synthetic-users): Synthetic users are AI agents given a persona (a background, goals and constraints) that stand in for real users in research or testing. - [Usability testing](https://www.stuntdouble.io/glossary/usability-testing): Usability testing watches people attempt real tasks in a product to find where they hesitate, make mistakes or give up. - [User persona](https://www.stuntdouble.io/glossary/user-persona): A user persona is a profile of a type of person a product serves: who they are, what they are trying to do, what they know already and what gets in their way. - [UX regression testing](https://www.stuntdouble.io/glossary/ux-regression-testing): UX regression testing checks, after every change, that the flows users depend on still work and still make sense, not only that the code still passes. ## Legal - [Privacy policy](https://www.stuntdouble.io/privacy): how we handle personal data. - [Terms of service](https://www.stuntdouble.io/terms): terms governing use of Stunt Double. - [Security](https://www.stuntdouble.io/security): our security posture and how to report a vulnerability. ## Recent blog posts - [Your Users may not be Human](https://www.stuntdouble.io/blog/your-users-may-not-be-human): In June 2026 Cloudflare confirmed machines now generate more web traffic than people. Every one of those visits is a user nobody has watched, and nobody can ask why. What does user-centred mean in this new age of AI? - [Building with Supabase](https://www.stuntdouble.io/blog/building-stunt-double-on-supabase): How we run a multi-tenant AI agent platform on Supabase: row level security for tenant isolation, OAuth and passkeys for humans and machines, pgvector for agent RAG, read replicas for global reads, and preview branches for every pull request. - [What Is MCP and Why It Matters for Product Teams](https://www.stuntdouble.io/blog/what-is-mcp-and-why-it-matters-for-product-teams): The Model Context Protocol lets AI assistants call tools in external services. For product teams, that means testing, feedback, and issue tracking without leaving your editor. - [Building a Self-Healing Product Feedback Loop](https://www.stuntdouble.io/blog/self-healing-feedback-loop): Turn error signals and feedback into almost instant product improvements with triage and cloud coding agents. - [For Humans & Their Machines](https://www.stuntdouble.io/blog/for-humans-and-their-machines): User-centred design in a world with AI agents. ## Optional - [Stunt Double Index](https://index.stuntdouble.io): independent benchmark of how AI agents experience the web. - [Status](https://status.stuntdouble.io): service status." }, "stepIndex": 41 } - 2026-09-30T00:26:22.999174+00:00 · tool_call · navigate
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- 2026-09-30T00:26:27.692861+00:00 · tool_call · navigate
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- 2026-09-30T00:26:35.40856+00:00 · tool_call · get_page_text
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<changefreq>weekly</changefreq> <priority>0.6</priority> </url> <url> <loc>https://www.stuntdouble.io/insights/why-your-regression-suite-misses-every-agent-driven-failure-mode</loc> <lastmod>2026-09-22T09:04:06.000Z</lastmod> <changefreq>weekly</changefreq> <priority>0.6</priority> </url> <url> <loc>https://www.stuntdouble.io/insights/mcp-is-already-in-your-product-what-australian-growth-teams-need-to-test-now</loc> <lastmod>2026-09-25T09:04:06.000Z</lastmod> <changefreq>weekly</changefreq> <priority>0.6</priority> </url> <url> <loc>https://www.stuntdouble.io/insights/four-signals-your-product-analytics-will-never-surface-but-agent-simulation-will</loc> <lastmod>2026-09-28T09:04:06.000Z</lastmod> <changefreq>weekly</changefreq> <priority>0.6</priority> </url> <url> <loc>https://www.stuntdouble.io/insights/designing-for-ai-agents-what-product-teams-need-to-know</loc> <lastmod>2026-09-29T23:59:57.000Z</lastmod> <changefreq>weekly</changefreq> <priority>0.6</priority> </url> <url> <loc>https://www.stuntdouble.io/insights/authors/michael-parker</loc> <lastmod>2026-09-30T00:20:35.843Z</lastmod> <changefreq>weekly</changefreq> <priority>0.6</priority> </url> </urlset>" }, "stepIndex": 47 } - 2026-09-30T00:26:43.394124+00:00 · tool_call · navigate
{ "step": { "ts": "2026-09-30T00:26:43.171Z", "kind": "tool_call", "name": "navigate", "input": { "url": "https://www.stuntdouble.io/pricing" } }, "stepIndex": 48 } - 2026-09-30T00:26:46.510284+00:00 · tool_result · navigate
{ "step": { "ts": "2026-09-30T00:26:45.044Z", "kind": "tool_result", "name": "navigate", "text": "Navigated to https://www.stuntdouble.io/pricing\nNow on https://www.stuntdouble.io/pricing (Pricing | Stunt Double)" }, "stepIndex": 49 } - 2026-09-30T00:26:47.850527+00:00 · screenshot
{ "stepIndex": 49 }
- 2026-09-30T00:26:55.39669+00:00 · tool_call · done
{ "step": { "ts": "2026-09-30T00:26:54.540Z", "kind": "tool_call", "name": "done", "input": { "message": "1. **Product Name, Value Proposition, and Target Persona:**\n - **Product Name:** Stunt Double\n - **One-Sentence Value Proposition:** \"Stunt Double’s actors drive a real browser through your product, prototype or Figma design, and show you authentic insights, backed by evidence.\" (Also stated as: \"Stunt Double sends AI users through your product to show how real people and AI agents actually experience it, so product, design and growth teams can fix what matters before they ship.\")\n - **Primary User Persona:** Product, design, and growth teams (as well as developers and product engineers testing preview deployments and flows).\n\n2. **Pricing, Headline Feature, and Free Trial:**\n - **Starter / Free Tier Price:** Free to try with no sign-up needed via the live demo (€0); the lowest self-serve tier is the **Solo Trial** at **€9 /mo** (or the **Hobby** tier at **€69 /team/mo**).\n - **Headline Feature:** AI actors driving a real browser through live sites, staging URLs, or Figma prototypes to run checklists and synthetic user interviews with step-by-step screenshots and evidence.\n - **Length of Free Trial Offered:** The site offers a **Solo Trial** for **up to 3 months** (at €9/mo), and a completely free live demo requiring no sign-up (the site does not state an expiration or time limit for the free live demo).\n\n3. **Enterprise Tier Access for Individuals & SSO Options:**\n - **Individual Access to Enterprise:** The site does not explicitly state whether an individual can purchase the Enterprise tier; it specifies Enterprise is \"Bespoke\" with \"Custom seats\" and is meant \"For organisations with specific needs\" (whereas \"Solo Trial\" is specifically designated for \"One person\" and Hobby for \"individuals and small projects\").\n - **SSO Options Listed for Enterprise:** Not stated. The pricing table and security page do not list specific Enterprise SSO options (such as SAML, Okta, Azure AD, etc.), noting only \"Custom\" integrations and direct security contact via NDA." } }, "stepIndex": 50 }