agentic validation skills

Manual test maintenance and brittle scripts lead to flaky CI pipelines and false positives. This skill implements the CIGE (Context, Intent, Guardrails, Execution) standard to manage agentic AI test cases that self-heal without compromising system safety. It forces a strict separation between what a test intends to achieve and the volatile execution steps used to get there.

What it does

• Standardize test authoring using the CIGE framework to separate stable intent from fragile execution steps.
• Automate failure classification by triaging results into infrastructure issues, stale logic, false positives, or actual product defects.
• Execute restricted self-healing through scoped procedures that can only mutate specific fields based on the failure type.
• Enforce guardrail integrity by ensuring safety constraints are never loosened or removed during the repair process.
• Manage human-in-the-loop approvals for any proposed changes to test intent or execution logic.

How to use this skill

1. Authoring mode: Provide a feature spec or existing test to generate a CIGE-compliant test case with stable Intent and mapped Execution IDs.
2. Classification mode: Input a test run log to identify the root cause using specRef and buildRef data.
3. Repair mode: Execute the specific recovery procedure (Recovery, Repair, or Escalation) mapped to the classification outcome.

Frameworks & tools

Works with any agentic testing framework or LLM-based QA runner. Requires access to versioned specifications (specRef) and build metadata (buildRef) for automated classification.

Why this beats prompting it yourself

Standard prompts often allow agents to "fix" tests by simply deleting failing steps or loosening safety checks. This skill enforces a rigid mutation policy where agents can only update the fields they are permitted to touch, preventing intent drift and maintaining strict security guardrails.

Use cases

• Refactoring brittle Selenium or Playwright scripts into adaptive agentic test cases.
• Triaging high volumes of test failures in CI/CD pipelines to separate infra flakes from real bugs.
• Safely updating test suites after UI refactors without manual rewrite of the entire test logic.

Known limitations

Classification is blocked if specRef or buildRef are missing. Procedures cannot remove guardrails. Requires one reference file load at a time.

https://www.amazon.science/publications/cige-an-agentic-ai-test-case-standard