Agent Skill

Visual QA skill

visual-qacode-yeongyu/oh-my-openagentpackages/shared-skills/skills/visual-qa/SKILL.md

Runs rigorous visual QA across web, terminal, and paginated surfaces: an Apple HIG-based checklist, paired light/dark captures at phone and desktop widths, screenshot evidence, and a per-item PASS/FAIL verdict. Use for any UI build or change, or when asked whether a page, component, or TUI looks right or follows the platform's design guidelines.

70k

always on

78 tokname + description

once used

8,656 tokSKILL.md body

bundled files

1816 scripts

repo stars

70kGitHub

Install the Visual QA skill

Skills CLI (Claude Code, Codex, Cursor and others)

npx skills add https://github.com/code-yeongyu/oh-my-openagent --skill visual-qa

Claude Code, by hand (all projects)

git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent.git /tmp/oh-my-openagent
mkdir -p ~/.claude/skills
cp -R /tmp/oh-my-openagent/packages/shared-skills/skills/visual-qa ~/.claude/skills/visual-qa

For one project only, copy the folder into .claude/skills/ in that project instead. The agent picks it up when a task matches its description.

What it costs your context

Agent Skills load in three steps. Tokens counted with the o200k tokenizer; your model's count will differ a little.

When	What loads	Cost
Every session	Name and description	78 tok
When the agent uses it	The SKILL.md instructions	8,656 tok
Only if opened	18 bundled files (57 KB)	varies

Until it is used, visual-qa costs about 17× less than the median MCP server we measured (1,362 tokens on every turn). Installing all 60 skills from code-yeongyu/oh-my-openagent would load 5,128 tokens of descriptions. Skills vs MCP study

Checks

Ships scripts the agent can run. Read them before installing.
The instructions are over 5,000 tokens, the Agent Skills specification's guideline for SKILL.md.

Checked 2026-10-22 · method

What's inside

The headings of its SKILL.md. Read the full file on GitHub.

Visual QA - Dual-Oracle Web and TUI Verification
Purpose and when to use
Step 1 - Detect the surface
Step 2 - Capture objective reference evidence
Reference packet hygiene
Coverage - capture every page, not a sample
Evidence must be fresh
Capture hygiene - validate before dispatching reviewers
Web
TUI
Motion and interaction capture
The checklist - every item PASS, FAIL or N/A, proven by a named capture
Step 3 - Dispatch two read-only QA subagents in parallel
Pass A - Design-system and functional integrity (deeper, strict)
Pass B - Visual fidelity and CJK precision (focused)
Step 4 - Synthesize one verdict
Completion gate - loop until an independent pass on fresh evidence
Step 5 - Reference-fidelity mode (when the task has a concrete visual target)
Reference evidence is not the verdict

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