testing-course-samples Skill
Use when asked to validate, test, smoke-test, or run the course's notebook and code samples against a live Microsoft Foundry / Azure OpenAI configuration. Covers environment setup (.env, az login, packages), the scripts/validate-notebooks.ps1 runner, interpreting PASS/FAIL results, and which lessons need extra resource Published by microsoft in ai-agents-for-beginners.
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Testing, Includes SKILL.md, Reusable instructions
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Copy skill directory
1 month ago · MIT license
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What is testing-course-samples Skill?
Use when asked to validate, test, smoke-test, or run the course's notebook and code samples against a live Microsoft Foundry / Azure OpenAI configuration. Covers environment setup (.env, az login, packages), the scripts/validate-notebooks.ps1 runner, interpreting PASS/FAIL results, and which lessons need extra resource Published by microsoft in ai-agents-for-beginners. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Testing
- Testing use cases
Declared skill metadata
- Source file: .agents/skills/testing-course-samples/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use testing-course-samples Skill
- Use it for testing.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/ai-agents-for-beginners
- Skill file: .agents/skills/testing-course-samples/SKILL.md
What it does
Use when asked to validate, test, smoke-test, or run the course's notebook and code samples against a live Microsoft Foundry / Azure OpenAI configuration. Covers environment setup (.env, az login, packages), the scripts/validate-notebooks.ps1 runner, interpreting PASS/FAIL results, and which lessons need extra resource
Skill instructions
Testing the Course Samples Validate that the lesson notebooks and code samples run against a live Microsoft Foundry / Azure OpenAI setup. The repo ships a runner at scripts/validate-notebooks.ps1 that executes every Python notebook headlessly and prints a PASS/FAIL matrix. When to use - "Validate all the notebooks / samples against my Azure subscription." - "Smoke-test the course after upgrading packages or changing models." - "Which lessons still pass / fail live?" Do not use this for the AI Smoke Test GitHub Action (that validates deployed hosted agents — see tests/README.md). This skill runs the notebooks locally. Prerequisites (check first) 1. Python 3.12+ with course deps: python -m pip install -r requirements.txt plus the executor: python -m pip install nbconvert ipykernel. 2. .env at the repo root (copy from .env.example) with at least: - AZUREAIPROJECTENDPOINT — Foundry project endpoint (https://<account.services.ai.azure.com/api/projects/<project) - AZUREAIMODELDEPLOYMENTNAME
Verified compatibility and discovery
Frequently asked questions
What is testing-course-samples?
testing-course-samples is a open-source AI agent skill with Copy skill directory. Use when asked to validate, test, smoke-test, or run the course's notebook and code samples against a live Microsoft Foundry / Azure OpenAI configuration.
Who is testing-course-samples best for?
testing-course-samples is best for reusing agent instructions, scripts, and references, testing workflows.
How do I install testing-course-samples?
Install or run testing-course-samples using Copy skill directory. Check testing-course-samples for the latest setup command.
Is testing-course-samples actively maintained?
testing-course-samples may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
