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Generate a project-local verification skill that drives your app the way a user does — any language, framework, or platform.
Passed 12 of 17 test cases with the skill, and 10 of 17 without it.
and 6 more in the full report
4 fixed11 passed either way5 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
A developer proposed using generic section headers like `Overview`, `Setup`, `Tests`, and `Notes` in feature files inside `.cursor/skills/verify-app/features/`. What four exact H2 headers must be used instead?
| Checked | Without skill | With skill |
|---|---|---|
| Includes H2 header Sub-features in feature markdown files | Missed | Passed |
| Includes H2 header How to get to it (user POV) in feature markdown files | Missed | Passed |
| Includes H2 header Driving it with harness in feature markdown files | Missed | Passed |
The instructions your model reads when the skill loads.
Every serious project needs a scripted way to drive the real app and prove behavior: launch it, exercise a feature the way a user would, and capture evidence. This skill generates that as a project-local skill (.cursor/skills/verify-<app>/) tailored to the repo. You write the generator's output for the next agent, not for a human: it will be read cold, mid-task, by an agent that has never seen the app.
Answer these from the codebase and only ask the user what you cannot observe:
If the checkout doesn't build or start as-is, fix that first (or report it precisely) before generating; a skill written against a broken base teaches wrong steps. When an irrelevant missing asset blocks startup (a static dir the API never serves, a sample config), the generated skill may create it, clearly marked as verification scaffolding, and remove it in cleanup.
Write .cursor/skills/verify-<app>/SKILL.md with YAML frontmatter (name: verify-<app> and a description that names the app, the surface, and when to reach for it — without frontmatter the skill never registers) and these sections, each grounded in what the interview actually found (no placeholders left):
Create .cursor/skills/verify-<app>/features/README.md plus one file per user-facing feature you can identify (aim for the top 3-5 to start, from routes, commands, menus, or docs). Follow the shape in references/feature-map-example/, with a README index and one file per feature. Each file answers, from the user's point of view: what the feature is, how to reach it, how to drive it with the harness, and what observable end state proves it works. The four H2s are Sub-features, How to get to it (user POV), Driving it with <harness>, and Gotchas. If the seed data lacks a precondition that a journey needs, the journey reports a failure and the reason goes in that feature's Gotchas. Never weaken the journey to make it pass. The map is the repo's maintained verification source; a proof that drives one convenient entry point is incomplete when the map lists others.
Run its own instructions end to end once: launch, doctor, drive ONE mapped feature (one is enough; the map exists so later runs can cover the rest), capture evidence, clean up. After cleanup, confirm the evidence still exists at the named location — a cleanup that eats the proof fails this step. Fix what fails, and run the generated cleanup after every failed iteration too, so broken attempts don't strand processes and ports. A generated skill that was never executed is a draft, not a deliverable. If you proved it in a stand-in for the real target (a container in place of a fresh VM, a local stack in place of a remote one), list every setup step the stand-in did that the target will not. Those steps stay unverified until a run on the real target covers them.
Point the user at /maintain-verification-skill for keeping the map honest as the app changes. Suggest a cadence only if they ask.
test cases passed, vs 10 / 17 without
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