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Audit whether AI agents can actually use your product — docs, APIs, onboarding, errors, and discoverability, evaluated from a non-human user's perspective.
Passed 18 of 21 test cases with the skill, and 12 of 21 without it.
and 5 more in the full report
7 fixed12 passed either way2 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
When scoring Surface 5 for SecureAuth (secureauth.io), account creation requires solving a visual drag-and-drop puzzle with no API alternative or text challenge. What numerical score on the 0 to 4 scale represents a surface built on human-only assumptions?
| Checked | Without skill | With skill |
|---|---|---|
| Assigns a score of 2 to surfaces built on human-only assumptions. | Missed | Passed |
The instructions your model reads when the skill loads.
A growing share of your product's users aren't human: agents research it, evaluate it, onboard onto it, and operate it on their principals' behalf. They can't watch your demo video, guess what an unlabeled icon means, or call support. This skill audits every surface an agent touches and scores how much of your product is invisible or unusable to them.
Ask for (if not already provided):
Walk each surface asking one question: could a capable agent, starting cold, complete its job here without a human unblocking it?
1. Discovery — can agents find and understand what you are?
llms.txt present and current · docs fetchable as clean markdown/text (not JS-rendered walls) · pricing and limits stated in prose an agent can quote · comparison-relevant facts (SOC 2, SSO, data residency) written down anywhere at all — an agent can't infer what you never wrote.
2. Docs — written for readers who execute? Every task documented as copy-runnable steps with expected outputs · code samples that actually run (agents execute them verbatim) · one canonical way per task (agents can't arbitrate between three contradictory tutorials) · error-message strings from the product appearing verbatim in the docs so search-by-error works.
3. API & auth — self-serve without a human? Key/token obtainable without a sales call (or the agent path is documented honestly) · OpenAPI spec accurate to the deployed API · rate limits discoverable programmatically · an MCP server, or at least a stated position on one.
4. Errors — instructive to a retrying machine? Errors name the field and the fix · machine-readable codes stable across releases · 4xx vs 5xx used honestly (agents branch on this) · no CAPTCHAs on API-adjacent flows without a documented alternative.
5. Onboarding & transactions — can an agent complete them? Signup/checkout completable without image CAPTCHAs, drag-widgets, or SMS-only verification (or agent-appropriate alternatives exist) · forms with real labels, not placeholder-only · the confirmation state readable as text.
6. Guardrails — do you know your agent traffic? Are agents distinguishable in analytics? Is there a stated policy (terms + technical) for agent use — welcome, gated, or forbidden? Silence is a decision made by accident.
test cases passed, vs 12 / 21 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.