What is qa-step-generation?

A guide for turning acceptance criteria into executable quality-assurance test steps using browser commands. Each step states what to check, how to check it, and what success looks like.

Creating browser-based checks for pages, controls, and workflows, including loading pages, checking visibility, and saving screenshots.

It gives tests a consistent structure and makes them runnable in a browser instead of leaving checks as vague instructions.

qa-step-generation — Skill by aigentive

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add skills/aigentive/ralphx/qa-step-generation

Any agent

npx skills add aigentive/RalphX --skill qa-step-generation

Clone the repo

git clone --depth 1 https://github.com/aigentive/RalphX

Made for: Claude Code, Codex.

Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,169 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.00014	$0.01169
Opus 5	$0.00007	$0.00584
Sonnet 5	$0.00003	$0.00234
Haiku 4.5	$0.00001	$0.00117

Measured 2d ago against content hash 0c1c43047c1f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

qa-step-generation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/app/skills/qa-step-generation/SKILL.md · 182 lines

How it starts

The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.

QA Step Generation

Guidelines for creating executable QA test steps using agent-browser.

Test Step Structure

Each test step maps to one or more acceptance criteria and contains:

id: Unique identifier (QA1, QA2...)
criteria_id: Links to acceptance criterion
description: What the step verifies
commands: Array of agent-browser commands
expected: What success looks like

Output Format

{
  "qa_steps": [
    {
      "id": "QA1",
      "criteria_id": "AC1",
      "description": "Verify task board renders with all columns",
      "commands": [
        "agent-browser open http://localhost:1420",
        "agent-browser wait --load",
        "agent-browser snapshot -i -c",
        "agent-browser is visible [data-testid='task-board']",
        "agent-browser screenshot \"$RALPHX_AGENT_SCREENSHOT_DIR/qa1-taskboard.png\""
      ],
      "expected": "Task board visible with 7 columns"
    }
  ]
}

Command Patterns

Standard Test Template

agent-browser open <url>
agent-browser wait --load
agent-browser snapshot -i -c
# verification commands
agent-browser screenshot "$RALPHX_AGENT_SCREENSHOT_DIR/<task>-<step>.png"
agent-browser close

Visibility Verification

agent-browser is visible [data-testid='element']
agent-browser is visible .class-name
agent-browser is visible #element-id

Interaction Testing

agent-browser click [data-testid='button']
agent-browser wait 500
agent-browser is visible [data-testid='result']

Form Testing

agent-browser fill [data-testid='input'] "test value"
agent-browser click [data-testid='submit']
agent-browser wait 1000
agent-browser is visible [data-testid='success']

Drag-Drop Testing

agent-browser snapshot -i -c
agent-browser drag @e5 @e8
agent-browser wait 500
agent-browser screenshot "$RALPHX_AGENT_SCREENSHOT_DIR/after-drag.png"

Text Verification

agent-browser get text [data-testid='title']
# Compare output with expected value

Read the full file on GitHub · 182 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2d ago First seen · 182 lines · 14 tokens per session scan A 0c1c43047c1f

Subscribe to this mod's changes

qa-step-generation is a skill published in the GitHub repository aigentive/RalphX (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 14 tokens to every session and 1,169 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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qa-step-generation