Dedica

Dedica is an agent readiness testing tool for websites. It tests your site the way AI agents use it and then gives your team a fix for every place those agents fail. The product is aimed at teams whose websites are visited, compared and signed up on by AI agents such as Muse, Dots, Instinct, ChatGPT, Claude, OpenClaw and GrokBot. A free score is delivered in under a minute with no signup required, and the detailed fix kit is purchased separately. Dedica's stated purpose is simple: find where agents get stuck on your site, and hand your team the fix. Most websites are built for people and fail for software. Dedica's site names the specific failure modes: bot checks, pages that only render in a browser, and APIs with no public docs. When an agent hits one of these, it does not report the problem — it simply moves on, which means the business never learns it was skipped. Dedica cites two figures to frame the stakes: only 6% of business websites are ready for AI agents, and businesses that are ready are recommended by AI agents 1.9× more often. The core problem Dedica addresses is that this failure is invisible by default; there is no error report when an agent quietly abandons a sign-up flow, so teams have to test for it deliberately. The free report runs 125 checks across four areas: discovery, access, usability and payments. Discovery asks whether agents can find what they need on your site at all. In the sample report this area is scored out of 20 and includes checks such as whether an OpenAPI or Swagger spec is published at the usual paths, and whether an MCP server or manifest can be found. The fix kit's file list shows further discovery-oriented items, including a check for an llms.txt file and an agent-friendly 404 page. Each discovery gap is a place where an agent has nothing machine-readable to work with, so the practical result of fixing them is that agents stop guessing and start reading structured information about your product, plans and endpoints. Access checks ask whether agents are let in once they find the right page. The sample report scores access out of 30, and the top-ranked issue in that sample is a bot check that blocks agents at sign-up: acme.com/signup returns a 403 challenge page. Dedica shows what the agent actually received — a challenge page with a reference ID — next to a comparable page that returns plans, prices and a working sign-up without a bot check. The fix instruction is explicit: let verified AI agents through the bot check on public pages and sign-up while keeping rate limits in place. OAuth support appears as another item in the fix kit, covering how agents authenticate rather than being turned away. Usability checks ask whether an agent can read and act on what it finds. This is the largest check group in the sample report, scored out of 40. One issue shown is pricing that needs JavaScript to load: acme.com/pricing is empty until scripts run, so an agent that fetches the page sees no plans or prices even though a human in a browser sees a full pricing table. Dedica contrasts this with a page it can use, where plans and prices sit in the page text and the sign-up action works. The corresponding fix file, 02-content-no-js.md, addresses rendering content without JavaScript. Usability work matters because an agent that cannot read your pricing cannot compare it, and an agent that cannot complete a sign-up cannot convert on your behalf. Payments is the fourth check area, scored out of 10 in the sample report. It covers whether an agent can get all the way through a commercial action — signing up for a plan, for instance — rather than being blocked at the last step. The sample report shows an overall score of 71 out of 100 with a grade of D, and 42 fixable issues spread across discovery (11/20), access (9/30), usability (14/40) and payments (4/10). Presenting the four sub-scores separately tells a team which layer of the problem to attack first rather than treating agent readiness as a single pass or fail. Every finding is ranked by how much fixing it would move the score. The report's Fix first list puts the highest-impact issues at the top with an estimated gain: a bot check blocking agents at sign-up (+6.2), pricing that needs JavaScript (+4.6), no OpenAPI spec published (+4.2), and no MCP server (+4.1). Each issue carries check points, such as 0/6, so a team can see how much of a given check is currently passing. The fix kit then turns each finding into one instruction file per issue, written for a developer or a coding agent, stating what to change and how to check it worked. In the sample, the kit contains 42 files, named so they map directly to the issue — 01-bot-detection.md, 02-content-no-js.md, 03-openapi-spec.md, 04-mcp-server.md, 05-llms-txt-exists.md, 06-oauth-support.md, 07-agent-friendly-404.md and 35 more. The workflow is scan, fix, scan again. First, you enter your domain; the score is free and takes under a minute. Second, you hand over the fix kit — either giving the files to your developer or pasting them into Claude Code, Codex, Cursor or GitHub Copilot. Third, once the change ships, you rescan and watch each check pass. The sample walks through exactly this loop, with a score of 38 turning into 71 after the fixes are applied. Because the fix files are written for coding agents as well as people, the same artifact can be routed into an existing agent-assisted development workflow without rewriting the instructions. The outcome Dedica describes is a site that agents can actually use: they find the pricing page, read the plans and open the sign-up flow, instead of hitting a 403 challenge page and silently giving up. Teams get a documented, per-issue record of what was wrong and how to verify the repair, which removes the guesswork from a class of problem that produces no error log. Dedica also frames the upside commercially — businesses ready for agents are recommended by AI agents 1.9× more often — so the work is positioned as revenue-relevant rather than purely technical hygiene. Concrete scenarios in the content include a team asking an agent to sign up for a plan and discovering the site blocks it; a pricing page that renders in a browser but arrives empty to an agent; and an API with no published spec or MCP server that leaves agents with nothing to call. The product suits teams shipping websites with pricing and sign-up flows, developers maintaining public APIs, and teams already using Claude Code, Codex, Cursor or GitHub Copilot who want remediation delivered as instructions those tools can execute. Pricing is explicit: the score with 125 checks is free, no signup is required, and the fix kit is $30 one-time per site. Dedica also lists Claude Code, Codex, Cursor and GitHub Copilot as ready targets for its fix files. In short, Dedica makes agent readiness measurable and fixable: it scores how agents find, read and use your website, ranks the issues that cost you the most, and hands your team an instruction file for each one so a developer or a coding agent can close the gap and verify the result on the next scan.