agentic-quality-engineering

agentic-quality-engineering is a skill for Claude Code, Codex from summarybotng/summarybot-ng. It costs 29 tokens per session (2,661 once invoked), scanned A, original, MIT.

AI agents as force multipliers for quality work. Core skill for all 19 QE agents using PACT principles.

Skill for Claude CodeCodex

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/summarybotng/summarybot-ng/agentic-quality-engineering
Any agent
npx skills add summarybotng/summarybot-ng --skill agentic-quality-engineering
Clone the repo
git clone --depth 1 https://github.com/summarybotng/summarybot-ng

Made for: Claude Code, Codex.

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 agentic-quality-engineering

README.md
[![agentmods](https://agentmods.dev/badge/skills/summarybotng/summarybot-ng/agentic-quality-engineering.svg)](https://agentmods.dev/skills/summarybotng/summarybot-ng/agentic-quality-engineering)
Your own site
<a href="https://agentmods.dev/skills/summarybotng/summarybot-ng/agentic-quality-engineering"><img src="https://agentmods.dev/badge/skills/summarybotng/summarybot-ng/agentic-quality-engineering.svg" alt="Measured on agentmods" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,661 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00029 $0.02661
Opus 5 $0.00015 $0.01331
Sonnet 5 $0.00006 $0.00532
Haiku 4.5 $0.00003 $0.00266

Measured today against content hash 127ba878f9d0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agentic-quality-engineering 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 today.

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.

.claude/skills/agentic-quality-engineering/SKILL.md · 340 lines

How it starts

The opening of the file, as written. The whole thing — 340 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agentic Quality Engineering

<default_to_action> When implementing agentic QE or coordinating agents:

  1. SPAWN appropriate agent(s) for the task using Task tool with agent type
  2. CONFIGURE agent coordination (hierarchical/mesh/sequential)
  3. EXECUTE with PACT principles: Proactive analysis, Autonomous operation, Collaborative feedback, Targeted risk focus
  4. VALIDATE results through quality gates before deployment
  5. LEARN from outcomes - store patterns in aqe/learning/* namespace

Quick Agent Selection:

  • Test generation needed → qe-test-generator
  • Coverage gaps → qe-coverage-analyzer
  • Quality decision → qe-quality-gate
  • Security scan → qe-security-scanner
  • Performance test → qe-performance-tester
  • Full pipeline → qe-fleet-commander

Critical Success Factors:

  • Agents amplify human expertise, not replace it
  • Human-in-the-loop for critical decisions
  • Measure: bugs caught, time saved, coverage improved </default_to_action>

Quick Reference Card

When to Use

  • Designing autonomous testing systems
  • Scaling QE with intelligent agents
  • Implementing multi-agent coordination
  • Building CI/CD quality pipelines

PACT Principles

Principle Agent Behavior Human Role
Proactive Analyze pre-merge, predict risk Set guardrails
Autonomous Execute tests, fix flaky tests Review critical
Collaborative Multi-agent coordination Provide context
Targeted Risk-based prioritization Define risk areas

19-Agent Fleet

Category Agents Primary Use
Core Testing (5) test-generator, test-executor, coverage-analyzer, quality-gate, quality-analyzer Daily testing
Performance/Security (2) performance-tester, security-scanner Non-functional
Strategic (3) requirements-validator, production-intelligence, fleet-commander Planning
Advanced (4) regression-risk-analyzer, test-data-architect, api-contract-validator, flaky-test-hunter Specialized
Visual/Chaos (2) visual-tester, chaos-engineer Edge cases
Deployment (1) deployment-readiness Release
Analysis (1) code-complexity Maintainability

Read the full file on GitHub · 340 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. today First seen · 340 lines · 29 tokens per session scan A 127ba878f9d0

Subscribe to this mod's changes

agentic-quality-engineering is a skill published in the GitHub repository summarybotng/summarybot-ng (2 stars, last pushed 2mo ago), licensed MIT. It adds 29 tokens to every session and 2,661 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 2026-09-03.

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