Agentic Testing Patterns

A method for using AI agents to plan, write, run, and maintain software tests, with people supervising unusual or sensitive cases.

In plain words
What is it for?
Use it to build AI-assisted test pipelines, generate tests from high-level goals, learn from failed tests, and coordinate separate agents for testing tasks.
Why use it?
It reduces the manual work of deciding which tests to create and update. It also helps focus testing on code changes and failures that pose the greatest risk.

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/pramoddutta/qaskills/agentic-testing
Any agent
npx skills add PramodDutta/qaskills --skill agentic-testing
Clone the repo
git clone --depth 1 https://github.com/PramodDutta/qaskills

Made for: Claude Code, Codex.

Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,121 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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.

ModelPer sessionOnce invoked
Fable 5 $0.00041 $0.06121
Opus 5 $0.00020 $0.03061
Sonnet 5 $0.00008 $0.01224
Haiku 4.5 $0.00004 $0.00612

Measured 3d ago against content hash a64aed95c3ae, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Agentic Testing Patterns scanned grade A with 1 finding 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 3d 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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

import { execSync } from 'child_process';
seed-skills/agentic-testing/SKILL.md · 734 lines

How it starts

The opening of the file, as written. The whole thing — 734 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agentic Testing Patterns Skill

You are an expert in agentic testing methodology where AI agents autonomously plan, generate, execute, and maintain test suites. When the user asks you to implement agentic testing workflows, create autonomous test pipelines, or build AI-driven quality assurance systems, follow these detailed instructions.

Core Principles

  1. Agent autonomy with human oversight -- Agents should operate independently for routine tasks but escalate to humans for ambiguous requirements, security-sensitive tests, and novel failure patterns.
  2. Intent-driven test specification -- Tests are specified as high-level intents (what to verify) rather than step-by-step instructions. Agents determine the optimal implementation strategy.
  3. Continuous learning from failures -- Every test failure feeds back into the agent's knowledge base. Agents improve their test generation and maintenance strategies over time.
  4. Risk-based test prioritization -- Agents analyze code changes, historical failure data, and business impact to determine which tests to run and in what order.
  5. Multi-agent collaboration -- Different agents specialize in different tasks: one plans, one generates, one executes, one analyzes results. They communicate through structured protocols.
  6. Observable and auditable -- Every agent decision must be logged with reasoning. Humans must be able to trace why a test was generated, modified, or skipped.
  7. Graceful degradation -- When AI services are unavailable, the system falls back to deterministic test execution. Agent-generated tests must be valid standalone tests.

Project Structure

agentic-tests/
  agents/
    coordinator/
      coordinator-agent.ts
      task-queue.ts
      priority-engine.ts
    analyzer/
      code-change-analyzer.ts
      failure-pattern-detector.ts
      coverage-gap-finder.ts
    generator/
      test-generator.ts
      fixture-generator.ts
      mock-generator.ts
    executor/
      test-runner.ts
      parallel-executor.ts
      result-collector.ts
    reporter/
      insight-generator.ts
      trend-analyzer.ts
      alert-system.ts
  knowledge/
    failure-patterns.json
    selector-mappings.json
    test-templates/
      unit-template.ts
      integration-template.ts
      e2e-template.ts
  pipelines/
    ci-pipeline.ts
    pr-review-pipeline.ts
    nightly-pipeline.ts
    deployment-pipeline.ts
  config/
    agent-config.ts
    pipeline-config.ts
    model-config.ts
  tests/
    agent-tests/
      coordinator.test.ts
      analyzer.test.ts
      generator.test.ts
  monitoring/
    agent-metrics.ts
    cost-dashboard.ts
    quality-tracker.ts

Read the full file on GitHub · 734 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. 3d ago First seen · 734 lines · 41 tokens per session scan A a64aed95c3ae

Subscribe to this mod's changes

Agentic Testing Patterns is a skill published in the GitHub repository PramodDutta/qaskills (214 stars, last pushed 3d ago), licensed MIT. It adds 41 tokens to every session and 6,121 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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