visual-qa

name

visual-qa

description

Rigorous visual QA for any UI you built or changed, across BOTH web/page UIs and TUI/terminal UIs. MUST USE after building or changing any UI to verify it visually before declaring it done. Captures objective reference evidence with a bundled diff script (image-diff for screenshots, tui-check for terminal captures), then runs two parallel read-only oracle passes (design-system and functional integrity; visual fidelity and CJK precision) and synthesizes one good/bad verdict. Triggers: visual QA, visual regression, screenshot diff, pixel diff, image comparison, UI looks wrong, design system check, is this really a design system or just an image, alpha channel breakage, responsive check, CJK text, Korean/Japanese/Chinese text clipping or semantic line breaks, baseline drop, glyph drop, TUI alignment, terminal UI, tmux capture, box-drawing border misalignment, wide-character column drift. Use it even when the user does not say visual QA but asks whether a page, component, or terminal layout looks right.

Visual QA - Dual-Oracle Web and TUI Verification

Verify a rendered UI against intent using objective script evidence plus two parallel read-only oracle passes, then synthesize one good/bad verdict. The script numbers focus the reviewers. They are not the verdict.

Purpose and when to use

• Use after you build or change any UI, before calling it done. Covers web/page UIs and TUI/terminal UIs.
• Use when output must match a mock, a baseline, or a stated design intent; when you suspect a regression; when CJK (Korean/Japanese/Chinese) text may clip, misalign, or wrap awkwardly; when a claimed design system might actually be a flat image; when a terminal layout may overflow or its borders may break.
• Skip when there is no rendered surface (pure backend or library logic with no visual or terminal output). For broad post-implementation review use review-work; this skill is the visual specialist.

In the commands below, $SKILL_DIR is this skill's own directory (the folder containing this SKILL.md). The bundled script lives at scripts/cli.ts inside it.

Step 1 - Detect the surface

• Web/page UI: renders in a browser (HTML/CSS/JS, components, canvas, SVG). Evidence is screenshots.
• TUI/terminal UI: renders as text in a terminal (box-drawing, panes, status lines, REPL/TUI apps). Evidence is terminal captures.

If the change touches both, run both capture tracks and feed both into the passes.

Step 2 - Capture objective reference evidence

Coverage - capture every page, not a sample

A surface is rarely one screen. If the UI has multiple pages, slides, routes, tabs, modal states, viewport breakpoints, or scroll positions, enumerate the COMPLETE set first and capture every one. A 40-slide deck means 40 captures, not 5. Never sample a few representative screens and generalize: the defect you miss is always on the page you did not open.

The verdict is per page. One failing page fails the whole surface, so "most pages look fine" is not a PASS. Record the enumerated list (page count and identifiers) so the reviewer in Step 3 can confirm nothing was skipped.

Evidence must be fresh

Every gate runs on captures produced AFTER the last edit to the rendered source. If any screenshot, PDF, capture, or QA JSON is older than the source file it claims to verify, it is stale and invalid - regenerate it before trusting it. Never report a PASS from an artifact you did not just produce against the current build.

Web

1. Capture a REFERENCE image: the user's mock/target, or a known-good baseline. Save as PNG.
2. Capture the ACTUAL rendered screenshot at the same viewport size using the project's browser tooling (the playwright, agent-browser, or dev-browser skill). Save as PNG. If none is configured or available, install agent-browser (bun add -g agent-browser && agent-browser install) and capture with it — see $SKILL_DIR/references/agent-browser-setup.md for the full setup, including how to shoot a fixed-viewport screenshot.
3. Run the diff and keep the JSON:

bun "$SKILL_DIR/scripts/cli.ts" image-diff <reference.png> <actual.png>

Key fields: dimensionsMatch, diffRatio (0..1), similarityScore (0..100), alphaChannelIntact, hotspots[] (grid regions ranked by diffRatio).

TUI

1. Capture plain text and an ANSI-preserving copy:

tmux capture-pane -p > capture.txt
tmux capture-pane -e -p > capture-ansi.txt

2. When the TUI evidence will be attached to a PR or reviewed visually, render the capture through the browser helper from the repository root:

node script/qa/web-terminal-visual-qa.mjs --title "TUI Visual QA" \
  --from-file capture.txt \
  --evidence-dir .omo/evidence/<slug>/tui-web-terminal

This produces terminal.png, terminal.html, terminal.txt, terminal-ansi.txt, and metadata.json. Treat this as the standard TUI visual artifact pattern for terminal screenshots. If the project is outside this repo, copy the same pattern: terminal capture -> browser-rendered page -> PNG + metadata with cleanup receipt.

3. Run the check with the REAL terminal width and keep the JSON:

bun "$SKILL_DIR/scripts/cli.ts" tui-check capture.txt --cols <N>

Key fields: maxWidth, overflowLines[], borderMisaligned, wideCharColumns[], hasAnsi.

This JSON (diff ratio, similarity score, hotspots or overflow lines, border alignment, wide-char columns, alpha) is REFERENCE evidence to aim the reviewers. It is not the verdict by itself.

Step 3 - Dispatch two read-only QA subagents in parallel

This independent review is REQUIRED before any "done" claim. Do not self-review inside the main agent and call the UI verified - a self-graded pass is the failure mode this step exists to stop. Dispatch it yourself, every time, without waiting to be told. Give each reviewer the captures for every enumerated page from Step 2, not a sample, and tell it the page count so it can confirm none were skipped.

Dispatch through your harness's own subagent tool. In OpenCode: task(subagent_type="oracle", ...). In Codex: multi_agent_v1.spawn_agent({"message": "...", "agent_type": "lazycodex-gate-reviewer", "fork_context": false}) (the code blocks below are written in OpenCode task(...) form; translate them to that spawn_agent call, putting the full prompt in message).

Send BOTH calls in a single message so they run concurrently. Each oracle is read-only: it reviews and reports, it cannot modify files. Each returns PASS, REVISE, or FAIL with concrete, located findings. Pass A proves the surface is a real design-system implementation, not a mock-only or faked-image substitute. Pass B directly opens screenshots and inspects source/content for visual and CJK defects.

Paste evidence directly into each prompt: source code, the plain-text TUI captures, the script JSON, and the screenshot paths plus your described observations for web. The two passes differ in depth by charter, not by any model or effort setting, which cannot be pinned per call.

Pass A - Design-system and functional integrity (deeper, strict)

task(subagent_type="oracle",
  run_in_background=true,
  load_skills=[],
  description="Visual QA pass A: design-system and functional integrity",
  prompt="""
REVIEW TYPE: DESIGN-SYSTEM AND FUNCTIONAL INTEGRITY (read-only)
TIER INTENT: Treat this as the deeper, stricter pass. Reason exhaustively before concluding. Assume a plausible-looking surface may be faked or mock-only until the source proves otherwise.

INTENT:
{What the user asked for, the mock or baseline, and the constraints.}

SURFACE: {web | tui | both}

SOURCE CODE:
{Full source of the UI: components, styles/tokens, layout, render code. Include neighboring files that show existing patterns.}

CAPTURES:
{Web: actual screenshot path(s) plus your described observations. TUI: paste capture.txt and capture-ansi.txt inline.}

SHARED SCRIPT EVIDENCE (reference, not verdict):
{Paste the image-diff or tui-check JSON. Use alphaChannelIntact for the transparency check.}

CHECK EACH:
1. Real design system vs ad-hoc/mock-only: are styles driven by coherent design tokens and reused primitives, or one-off hardcoded values scattered per element? Treat mock-only screens, static compositions, or one-page hardcoded styling with no reusable system as BLOCKING unless the user explicitly requested a throwaway mock.
2. Faked-with-an-image anti-pattern: is the UI a real DOM/component tree, or a pasted raster/screenshot or background-image standing in for live elements? For TUI: a real layout that reflows, or hardcoded pre-rendered text at fixed widths?
3. Alpha and transparency: handled correctly, with no unexpected opaque or black fills and correct PNG/CSS alpha? Cross-check alphaChannelIntact.
4. Code style and implementation quality.
5. Responsive and resize behavior across viewport sizes (web) or terminal resize (TUI).
6. Do the user-intended FEATURES actually work: interactions, states, navigation (web); input handling, resize, scroll (TUI)? Trace the code paths.

OUTPUT:
VERDICT: PASS | REVISE | FAIL
CONFIDENCE: HIGH | MEDIUM | LOW
SUMMARY: 1-3 sentences
FINDINGS: for each, [dimension] [severity] what is wrong, where (file/line or capture region), and the concrete fix
WHAT IS GOOD: correct aspects that must not regress
BLOCKING: items that must be fixed; empty if PASS
"""
)

Pass B - Visual fidelity and CJK precision (focused)

task(subagent_type="oracle",
  run_in_background=true,
  load_skills=[],
  description="Visual QA pass B: visual fidelity and CJK precision",
  prompt="""
REVIEW TYPE: VISUAL FIDELITY AND CJK PRECISION (read-only)
TIER INTENT: Treat this as the focused visual pass. Directly open the screenshots with the available image-viewing tool (`view_image`, `look_at`, or browser inspection) before judging. Anchor every claim to the script evidence, source code, and captures.

INTENT:
{What the user requested and the mock or baseline to match.}

SURFACE: {web | tui | both}

CAPTURES:
{Web: actual and reference screenshot paths plus your described observations. TUI: paste capture.txt and capture-ansi.txt inline.}

SOURCE CODE:
{For web: include the rendered text/content, components, typography, layout, and style code. For TUI: include render code that controls wrapping, width, and wide-character handling.}

SCRIPT EVIDENCE (required, consume every field):
{Paste the image-diff or tui-check JSON.}

USE THE EVIDENCE:
- Web (image-diff): start from diffRatio and similarityScore, then directly open every screenshot path and inspect every hotspots[] entry (gridX, gridY, x, y, width, height, diffRatio). Explain the visual cause of each flagged region from the pixels and source/content together.
- TUI (tui-check): inspect maxWidth vs expectedColumns, every overflowLines[] entry, borderMisaligned, and wideCharColumns[].

CHECK:
1. Does the rendered output match what the user requested: layout, spacing, color, type, alignment?
2. CJK precision:
   - Web: natural CJK line breaking for display and body text. Inspect every page's screenshot for this, not a sample. A high `similarityScore` never excuses a break: each class below is REVISE/FAIL and blocking regardless of similarityScore. Flag every one of:
     - a particle or ending orphaned onto its own line, for example `핵심 자료 / 도` or `끝에서 / 만난다`.
     - a short subject or topic phrase split from its predicate, for example `두 강은 / 끝에서 만난다` (the whole clause should sit on one line).
     - a connective or auxiliary expression split mid-phrase, for example `쓸 수 / 있지만` or `방 / 식이`.
     - a parenthetical or source/citation English string broken across lines, for example `(Vaswani et al. 2017, Attention Is / All You Need)` or `(Schulman et al. 2017); AlphaGo (Silver et al. / 2016)`.
     - oversized headings or narrow containers that create orphaned one-character or final-syllable lines, split Korean/Japanese/Chinese semantic phrases unnaturally (for example `놀라운 변 / 화`), detach labels such as `[Image #1]` from their content, clip baselines/descenders, drop glyphs (tofu), or show font metric mismatch. Treat screenshot patterns like `에이전트 오케스트 / 레이션 현황 및 미 / 래` as REVISE/FAIL, not acceptable wrapping.
   - TUI: wide-character column drift (CJK cells counted as 1 instead of 2), box-drawing border misalignment, content overflowing past the terminal width.

OUTPUT:
VERDICT: PASS | REVISE | FAIL
CONFIDENCE: HIGH | MEDIUM | LOW
SUMMARY: 1-3 sentences
EVIDENCE TRACE: each hotspot or overflow line mapped to its visual cause
FINDINGS: for each, [severity] what is wrong, where (hotspot grid or capture line:col), and the concrete fix
BLOCKING: items that must be fixed; empty if PASS
"""
)

Step 4 - Synthesize one verdict

When both passes return, merge them into a single report. Per dimension, mark good or bad with evidence. For each bad item, state what is wrong, where (file/line, hotspot grid, or capture line), and the concrete fix. Call out what is genuinely good so it is not regressed later.

Completion gate - loop until an independent pass on fresh evidence

This is a hard stop rule, not a guideline. The UI is NOT done until ALL of these hold at once on the SAME current build:

• An independent read-only reviewer subagent returned PASS with no BLOCKING findings.
• That reviewer judged a FRESH capture of every enumerated page from Step 2 - no stale artifacts, no skipped pages.
• Every CJK and layout finding is resolved in the rendered output, not merely noted.

If any page fails, you are not done: fix it, re-capture the full set, re-dispatch the reviewer, and repeat. Loop until the independent reviewer passes on the current build. Do not stop because the automated script reports zero issues - the script aims the reviewer, it does not replace it, and it routinely passes text while the rendered page is still broken. Do not stop because an earlier pass approved an older build. The only non-loop exit is to list the exact remaining gaps and get explicit user acceptance; never self-certify a silent PASS.

# Visual QA - Verdict: GOOD | NEEDS WORK

| Dimension | Pass | Verdict | Evidence |
|---|---|---|---|
| Design system real vs faked | A | good/bad | ... |
| Features work | A | good/bad | ... |
| Responsive / resize | A | good/bad | ... |
| Alpha / transparency | A+B | good/bad | ... |
| Visual fidelity to intent | B | good/bad | ... |
| CJK precision | B | good/bad | ... |

## Must fix
[Blocking items, each with location and fix, in priority order]

## Good, keep it
[Correct aspects that must not regress]

## Completion gate
[Satisfied, or the exact remaining gaps and who accepted them]

Step 5 - Clone-coding mode (when the task was a clone or design port)

Run this step IN ADDITION to Steps 1-4, but ONLY when the original user task was a clone or design port: "clone this site", "move this Figma design to code", "rebuild this screen", "make it look exactly like X". For these tasks the normal dual-oracle is necessary but NOT sufficient. After it returns, run the following TWO additional MANDATORY verifications and LOOP until BOTH pass.

1. Pixel-perfect design-compare subagent (visual oracle). Dispatch a focused, read-only design-compare reviewer (recommend gpt-5.5 with medium reasoning). It must crop/zoom BOTH the reference (the target / Figma export / source-site screenshot) and the ACTUAL screenshot into matching regions and read them pixel-by-pixel - header, nav, each card, spacing, type ramp, color tokens - not at a glance. Anchor every claim with the bundled tool:

bun "$SKILL_DIR/scripts/cli.ts" image-diff <reference.png> <actual.png>

It judges whether layout geometry, spacing, design tokens (color, type, radius, shadow), and the design itself are identical to the target, region by region. Anything off by more than rounding is a finding.

2. Code-level design-system fidelity (code oracle). Call the code-quality reviewer named EXACTLY lazycodex-clone-fidelity-reviewer (spawn it by that agent name). It verifies the implementation is a RIGOROUS design-system build - a real component tree, real design tokens, reused primitives - and is NOT a pasted image, a screenshot or background-image substitute, or a hardcoded one-off that merely looks right in one screenshot. If that named reviewer is not installed in this harness, fall back to an inline rigorous code review against the SAME criteria.

RULE (mandatory, non-negotiable): the clone is NOT done until BOTH the pixel-compare AND the lazycodex-clone-fidelity-reviewer (or its inline fallback) confirm that the layer structure, the design system, and the design itself are strictly identical to the target. If EITHER fails, it is a MANDATORY retry: re-implement the gaps and re-run BOTH verifications from the top. Repeat the retry loop until both pass on the same revision. Never declare a clone complete on a single pass, on visual-only evidence, or on code-only evidence - both oracles must confirm on the same build.

Reference evidence is not the verdict

The script quantifies pixels and columns. It cannot judge whether the result is a real design system, whether features work, or whether intent was met. A 99/100 similarityScore can still hide a pasted-image fake, a broken interaction, or clipped CJK descenders. Use the numbers to aim the oracles, then trust the synthesized review.

Illustrative output (locked field names):

{
  "command": "image-diff",
  "dimensionsMatch": true,
  "reference": { "width": 1440, "height": 900 },
  "actual": { "width": 1440, "height": 900 },
  "totalPixels": 1296000,
  "diffPixels": 38880,
  "diffRatio": 0.03,
  "similarityScore": 97,
  "alphaChannelIntact": true,
  "hotspots": [
    { "gridX": 2, "gridY": 0, "x": 960, "y": 0, "width": 480, "height": 300, "diffRatio": 0.21 }
  ],
  "summary": "97/100 similarity; one hotspot in the top-right header region."
}

{
  "command": "tui-check",
  "expectedColumns": 80,
  "lineCount": 24,
  "lineWidths": [80, 80, 82, 80],
  "maxWidth": 82,
  "overflowLines": [ { "line": 3, "width": 82 } ],
  "borderMisaligned": true,
  "wideCharColumns": [12, 13],
  "hasAnsi": false,
  "summary": "Line 3 overflows 80 cols by 2; borders misaligned at wide-char columns 12-13."
}