home / skills / oimiragieo / agent-studio / test-skill-e2e-1771181741284

test-skill-e2e-1771181741284 skill

/.claude/skills/test-skill-e2e-1771181741284

This skill validates knowledge base indexing, tests search functionality, and verifies CSV schema to ensure reliable E2E knowledge base performance.

npx playbooks add skill oimiragieo/agent-studio --skill test-skill-e2e-1771181741284

Review the files below or copy the command above to add this skill to your agents.

Files (1)
SKILL.md
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---
name: test-skill-e2e-1771181741284
category: testing
description: Test skill for E2E knowledge base validation
tags:
  - testing
  - e2e
  - validation
---

# test-skill-e2e-1771181741284

<identity>
Test skill for E2E validation of knowledge base indexing system.
</identity>

<capabilities>
- Validates knowledge base indexing
- Tests search functionality
- Verifies CSV schema
</capabilities>

<instructions>
This is a test skill created for E2E testing. It should be indexed and searchable.
</instructions>

Overview

This skill is a lightweight test tool for end-to-end validation of knowledge base indexing and search. It is designed to be indexed and discovered by a knowledge base system to confirm ingestion, schema validation, and retrieval behavior. Use it to validate pipelines without relying on production content.

How this skill works

The skill registers a simple set of test artifacts and metadata that an indexing system should consume. It asserts that CSV schema fields match expected shapes, validates that documents become searchable, and runs basic search queries to confirm retrieval. Results are presented as pass/fail checks so you can quickly spot ingestion or search regressions.

When to use it

  • Validate a new or updated indexing pipeline before deployment
  • Run periodic smoke tests of knowledge base ingestion and search
  • Verify CSV schema compatibility and field mapping
  • Confirm search queries return expected test documents
  • Troubleshoot indexing failures after system changes

Best practices

  • Run this skill in a staging environment that mirrors production settings
  • Include it in continuous integration or scheduled validation jobs
  • Keep test CSVs and expected search queries minimal and stable
  • Record and track pass/fail outcomes to detect regressions over time
  • Combine with log and metric checks for deeper troubleshooting

Example use cases

  • Smoke test a knowledge base after upgrading the indexer or search engine
  • Verify new CSV ingestion code preserves required schema fields
  • Confirm search relevance after changing tokenizer or ranking parameters
  • Automate nightly validation to detect transient ingestion issues

FAQ

What does this skill check in the CSV?

It verifies that required columns exist and conform to expected names and basic data types so the indexer can map fields correctly.

How are search validations performed?

The skill runs predefined queries against the indexed test documents and asserts that expected documents are returned within configured result windows.