Agent-first screenshots — an agent drives the real app via CDP and produces clean, defect-free product screenshots (newsletters, landing pages, social, decks, PR). Dual-channel verification (DOM + pixels + vision) in a capture loop. Use for any "take/redo screenshots of the app" task.
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An agent-first screenshot is produced by an agent driving the real app via CDP, gated by structural + pixel + vision verification before it ships. It turns screenshots from hand-crafted artifacts into a regenerable pipeline.
Use this for "take/redo screenshots / make marketing images" tasks. It is NOT
e2e evidence — for pass/fail proof use the fraimz skill.
A shippable screenshot has ZERO obvious visual defects — the bar is not "the content is present", it is: would a human glancing at it immediately spot something broken? Overlapping or clipped text, misaligned/collapsed layout, garbled or mid-transition content, blank regions, stray modals/tooltips — any of these disqualifies the frame. Full stop.
Operate the app like a power user preparing a demo, not like a developer hacking the DOM. The app already looks great: get it into a real, settled state through the UI and capture it cleanly. Never rebuild or fake it.
display:none is safe. Never
inject fake HTML, override flex/height/width on structural containers, add
fixed-position overlays, or mutate the DOM tree — the layout engine will
collapse (scroll areas shrink to 0, content disappears).location.reload(), wait for
full render, navigate through the UI, minimal leaf cleanup, verify, capture.
Never carry CSS hacks across shots.deviceScaleFactor: 2), then wait ~1s and re-verify — the override can
trigger re-layout.innerText existing does not mean visible; a healthy DOM rect does not mean it
rendered. Every frame must pass all three before it ships:
DOM pre-check (cheap, before capture): scroll area height > 100px (not collapsed), hero text inside the viewport rect, no unexpected modal/overlay. If it fails: reload and redo — never fix with more CSS.
Pixel post-check (truth, after capture): decode the PNG and sample the
DOM-derived hero rects. Calibration: for text-on-white UI, background ratio
is a bad signal (85–92% background is normal). Variance is the reliable
signal: content-filled region variance > ~200 (often 1000+); blank/flat
region < 50. Whole-image bgRatio > 0.97 → blank frame.
Vision check (mandatory gate): deterministic stats CANNOT catch the defects that matter most — overlap, clipping, misalignment, double-rendering. Hand the PNG to a vision-capable model with a zero-defect rubric returning JSON:
{ any_obvious_defect: bool, // the gate — if true, REJECT
overlapping_text_or_elements: bool, clipped_or_cutoff: bool,
misaligned_or_broken_layout: bool, blank_or_empty_regions: bool,
stray_modal_tooltip_or_panel: bool, legible: bool,
polish_score: 1-5, defects: ["..."] }If any_obvious_defect is true the frame is rejected regardless of layers
1–2. Diagnose, fix the root cause (settle the state, close the picker,
reload), recapture.
Reusable scripts in this skill's directory: screenshot-verify.mjs (verify an
existing PNG) and capture-verify.mjs (capture at 2x + verify regions + save
only on pass); both use sharp.
| Symptom | Fix |
|---|---|
| Overlapping/clipped text (layers 1–2 pass) | Unsettled/edit-mode/wrong-width state — settle, use preview mode, gate on vision |
| Blank screenshot / 32px scroll area | Structural element was CSS-hidden — reload, close panels via UI |
| Overlay (picker/modal) on every shot | It was opened and never closed — Escape before capturing |
| In DOM but not in pixels | Clipped/blank render — trust variance + vision, not innerText |
Injecting fake components; overriding flex properties; fixed-position
overlays; carrying state across shots; verifying via innerText only;
proof-frame mindset (the goal is "I want that", not "it didn't crash").
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