Ax‑Check.com Launch: Automated Agent‑Onboarding Audits for SaaS Products

Ax‑Check.com automates the "agent experience" audit

Ax‑Check.com runs three independent agents through a product’s onboarding flow and returns a score with actionable recommendations. The service is aimed at SaaS teams that want to ensure their APIs, CLIs, marketing sites, and developer portals are discoverable and usable by autonomous AI agents.

How the audit works

The platform crawls the supplied domain, extracts any public documentation, CLI installers, and marketing content.
Three sandboxed agents attempt an end‑to‑end onboarding: signing up, installing a CLI or SDK, and performing a minimal task.
Each agent records failures, friction points, and missing information. The results are aggregated into a numeric score (0‑100) and a list of concrete fixes.
Scores are displayed on a public leaderboard, allowing companies to benchmark against peers such as Supabase, PostHog, and Clerk.

What the score tells you

A‑grade (90‑100) – Documentation is fully machine‑readable, CLI/MCP install steps are clear, and pricing information is unambiguous. Examples: Kernel.sh, Loops.so, Increase.com.
B‑grade (70‑89) – Core setup works but some assets (e.g., Markdown on the homepage, pricing clarity) are missing. Examples: Timely, Goodmem, Sipgate.
F‑grade (0‑69) – Agents cannot locate usable docs or encounter blockers such as 403 responses, missing API keys, or non‑standard file formats. Example: Vyxal’s bare homepage scores 0.

Why the tool matters now

Agentic AI is becoming a first‑class consumer. Large language models (LLMs) are increasingly used to automate workflows, and they rely on well‑structured, machine‑readable documentation.
Hidden friction surfaces quickly. Human testers often overlook subtle issues like missing User‑Agent headers or non‑standard CLI prompts that block automated agents.
Competitive benchmarking. The public leaderboard shows which companies have already optimized for agents, providing a clear incentive to improve.

Community insights from Hacker News

"Integrating live bots to demonstrate live visitor experiences is a nice touch. I hit a blocker where the default Python urllib User‑Agent gets a 403 from anc.dev. Can you expose the scripts the agents generate?" – brettdav

This comment highlights two practical concerns: (1) the importance of transparent agent scripts for debugging, and (2) the need for sites to handle generic user‑agents without rejecting them.

"How do you think about enabling fully agentic onboarding without proper human identification? It feels like any rate limiting would be pretty easy to get around." – the1024

The observation raises security considerations. If agents can bypass rate limits, services must implement robust bot‑detection that does not impede legitimate AI agents.

"Nice! This should help in making my stuff as inaccessible as possible to agents." – eliaspro

A tongue‑in‑cheek reminder that some developers may deliberately obfuscate their APIs to prevent automated scraping; Ax‑Check makes such gaps visible.

"Going to try this out for our MCP" – Farbod_memarian

Shows early adoption interest from teams building Managed Cloud Platforms (MCPs) who need to verify that their onboarding is agent‑friendly.

"I've been seeing these pop up recently, I think I saw Mintlify launch one too. Why the sudden increase in attention towards coding agents?" – mastrchief117

Reflects a broader industry trend: more developer tools are exposing LLM‑driven agents, prompting a need for systematic audit tools.

Practical steps to improve your Ax‑Check score

Provide machine‑readable docs – Offer OpenAPI specs, Markdown files, or JSON schemas that agents can parse without HTML scraping.
Standardize CLI installation – Use common package managers (npm, pip, Homebrew) and ensure the installer works without interactive prompts.
Expose pricing clearly – Include a dedicated pricing page with structured data (priceSpecification) so agents can retrieve cost information.
Allow generic User‑Agents – Do not block default Python urllib or curl agents; respond with the same content as browsers.
Test with multiple agents – Run the Ax‑Check audit regularly and also manually with tools like curl, httpie, and headless browsers to catch edge cases.

Limitations and open questions

Domain‑only scope – The service currently requires a full domain; it cannot target a specific sub‑directory, which some commenters found restrictive.
Binary auditing – While the founder mentioned plans to audit CLI binaries, the public UI presently focuses on web‑based onboarding.
Transparency of agent scripts – Users have requested access to the exact scripts the agents execute to reproduce failures; this feature is not yet available.

Bottom line

Ax‑Check.com offers a concrete, automated way to measure how ready a product is for the emerging class of autonomous AI agents. By surfacing hidden onboarding friction and providing a public benchmark, it pushes SaaS teams to adopt agent‑friendly documentation practices—an essential step as AI‑driven automation becomes mainstream.