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ac-qa-e2e-review

ac-qa-e2e-review is a skill for Claude Code from WaterplanAI/agentic-config. It costs 40 tokens per session (717 once invoked), scanned A, original, MIT.

A review workflow that checks a software specification against a working website in a real browser using Playwright, a browser-testing tool.

In plain words
What is it for?
Use it to test each stated objective, take screenshots, and record whether the page behaves and looks as required.
Why use it?
It provides visual evidence that the implementation meets the written requirements instead of relying only on code inspection.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument.

Part of the agentic-config plugin — 49 skills, 1 plugin shipped together

not rated 30repo 1mo ago A scan 40 tokens original MIT

Good fit Use it to test each stated objective, take screenshots, and record whether the page behaves and looks as required.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/waterplanai/agentic-config/ac-qa-e2e-review
View source ↗ WaterplanAI/agentic-config
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.

Any agent
npx skills add WaterplanAI/agentic-config --skill ac-qa-e2e-review
Clone the repo
git clone --depth 1 https://github.com/WaterplanAI/agentic-config

Made for: Claude Code.

Or install agentic-config, the plugin that ships this one along with the rest of its 49 skills, 1 plugin.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ac-qa-e2e-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/waterplanai/agentic-config/ac-qa-e2e-review/github.svg)](https://agentmods.dev/skills/waterplanai/agentic-config/ac-qa-e2e-review)
Your own site
<a href="https://agentmods.dev/skills/waterplanai/agentic-config/ac-qa-e2e-review"><img src="https://agentmods.dev/badge/skills/waterplanai/agentic-config/ac-qa-e2e-review/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ac-qa-e2e-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/waterplanai/agentic-config/ac-qa-e2e-review"><img src="https://agentmods.dev/badge/skills/waterplanai/agentic-config/ac-qa-e2e-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 717 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.00717
Opus 5 $0.00020 $0.00358
Sonnet 5 $0.00008 $0.00143
Haiku 4.5 $0.00004 $0.00072

Measured 10d ago against content hash 504378544c79, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ac-qa-e2e-review 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 10d 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.

packages/pi-ac-qa/skills/ac-qa-e2e-review/SKILL.md · 103 lines

How it starts

The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.

E2E Spec Review Command

Validate implementation against spec requirements using browser-based visual proof.

Spec File: $1 Base URL: $2 (default: http://localhost:${DEFAULT_PORT:-5173}/)

Pre-Flight Checks

  1. Verify Spec File Exists

    • Read spec file from $1
    • If not found: STOP with "Spec file not found: $1"

  2. Verify playwright-cli Installed

    • Run: playwright-cli --help
    • If not available: STOP with "playwright-cli not installed. Run: npm install -g @playwright/cli@latest"

  3. Parse Spec Requirements

    • Extract MLOs (Mid-Level Objectives) from Human Section
    • Extract acceptance criteria from Details section
    • Create validation checklist

Execution

  1. Initialize Review Session

    • Create output directory: {PROJECT_ROOT}/outputs/review/<spec-id>/
    • Record review start timestamp

  2. Open Application

    • Navigate to base URL: playwright-cli open <base_url>
    • Take initial screenshot: playwright-cli screenshot --output {PROJECT_ROOT}/outputs/review/<spec-id>/01_initial.png
    • Verify application loads successfully

  3. Validate Each MLO

    • For each Mid-Level Objective: a. Navigate to relevant UI section b. Take screenshot of current state c. Verify visual elements match expected d. Test interactions if applicable e. Document pass/fail with evidence

  4. Capture Visual Proof

    • Screenshot key states during validation
    • Name format: <NN>_<mlo>_<state>.png
    • Example: 02_mlo1_button_visible.png

  5. Generate Review Summary

Output Format

Generate markdown review summary:

# Review: <spec-title>

**Spec:** $1
**Date:** <ISO date>
**Status:** PASSED | FAILED | PARTIAL

## MLO Validation

### MLO-1: <title>
- Status: PASSED/FAILED
- Evidence: ![screenshot]({PROJECT_ROOT}/outputs/review/<spec-id>/02_mlo1.png)
- Notes: <observations>

### MLO-2: <title>
...

## Screenshots

| # | Description | Path |
|---|-------------|------|
| 1 | Initial load | {PROJECT_ROOT}/outputs/review/<spec-id>/01_initial.png |
| 2 | MLO-1 validation | {PROJECT_ROOT}/outputs/review/<spec-id>/02_mlo1.png |

## Video Recording

Full session: {PROJECT_ROOT}/outputs/e2e/<timestamp>-review-<spec-id>.webm

## Summary

<brief summary of findings>

Read the full file on GitHub · 103 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.

  1. 10d ago First seen · 103 lines · 40 tokens per session scan A 504378544c79

Subscribe to this mod's changes

ac-qa-e2e-review is a skill published in the GitHub repository WaterplanAI/agentic-config (30 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 717 once invoked, about $0.0002 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 2026-08-30.

Browser automationClaude CodeE2E testingTestingagenticaiconfigcursorworkflow
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