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Running Release Tests

OrganizationPopular
aws
running-release-tests

Run automated release testing (UI or API) via the AWS DevOps Agent using a pre-configured test profile. Use when the user wants to validate multi-step workflows, verify features, check for regressions, or test API endpoints. Trigger words include run tests, UAT, test my app, test profile, UI test, API test, automated testing, regression test, QA, end-to-end test, run the QA agent.

Overview

Publisheraws
Repositoryagent-toolkit-for-aws
Skill namerunning-release-tests
Stars
2.7K
Forks
311
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by aws on GitHub. Read the source before you install it.

Installation

Install the Running Release Tests AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git /tmp/agent-toolkit-for-aws
mkdir -p .claude/skills
cp -r /tmp/agent-toolkit-for-aws/plugins/aws-agents-for-devsecops/skills/running-release-tests .claude/skills/running-release-tests
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Running Release Tests in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Running Release Tests on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Running Release Tests is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Release Testing

AgentSpace routing (SigV4 only): If list_agent_spaces is available in your tool list and the multi-space orchestration skill has NOT been invoked yet this session, invoke it first to determine which agent_space_id to use. Then pass agent_space_id on all tool calls below. For bearer token auth this is unnecessary — the token is already scoped to one space.

Run automated release testing in the cloud via the AWS DevOps Agent's Release Testing Agent. Supports UI testing (browser-based) and API testing (OpenAPI spec-based). Uses pre-existing test profiles that define target URL, agent type, personas, and credentials.

Input is a test profile — the test profile already contains the target URL, agent type (UI or API), test personas, and credentials. Do NOT ask the user for a URL directly; the URL is defined in the test profile.

Prerequisites

  • A pre-existing test profile (Knowledge Item ID like ki-12345) created from the AWS DevOps Agent console

Gathering test parameters

Before starting any workflow, you MUST gather the following parameters. Do NOT proceed to job creation until answered.

Step 1 — Test profile (required)

Ask the user which test profile to use. The test profile already contains the target URL, agent type (UI or API), test personas, and credentials configuration — these do NOT need to be gathered separately.

Note: A pre-existing test profile is a prerequisite. Test profiles are created using the AWS DevOps Agent console or API, not through this tool. If the user asks whether one can be created here, inform them it must already exist.

Step 2 — Test requirement (optional)

If the user has not already mentioned a test focus, ask:

"Do you have a specific test requirement or focus area? If not, I'll run a full exploratory test."

Wait for the user's response. If they provide one, use it as the test_requirement. If they say no or skip, proceed without it.

IMPORTANT: You MUST wait for the user to respond before proceeding to job creation.

Core workflow

1. Select Agent Space

List available agent spaces:

aws devops-agent list-agent-spaces --region us-east-1

Present the list to the user and ask which agent space they'd like to use. Do NOT proceed until the user has selected one. Use the selected agentSpaceId as SPACE_ID in all subsequent calls.

2. Check tool availability

Verify that the following tools are available: aws_devops_agent__create_release_testing_job, aws_devops_agent__get_task, aws_devops_agent__list_journal_records, aws_devops_agent__get_release_ui_testing_report, aws_devops_agent__get_release_api_testing_report. These tools are NOT deferred/lazy-loaded — if they do not appear in your tool list, they are unavailable. Do NOT search for them via ToolSearch. If any are missing, skip the remaining steps in this section and use the "Fallback (aws-mcp)" path below instead.

3. Start the Job

aws_devops_agent__create_release_testing_job(
    test_profile_id="ki-12345",
    webhook_event_message="<optional test requirement>"
)
→ {"taskId": "...", "executionId": "...", "status": "started"}

Record the taskId and executionId from the response.

4. Poll for Status

Call aws_devops_agent__get_task(task_id=TASK_ID) every 30 seconds until the status transitions to IN_PROGRESS or a terminal state.

5. Monitor Until Completion

Once IN_PROGRESS, poll for progress in a loop:

  1. Call aws_devops_agent__list_journal_records(execution_id=EXEC_ID, order="ASC") to fetch new findings.
  2. Present each record to the user with a friendly progress update.
  3. Use next_token from the response to fetch only new records on subsequent polls.
  4. Wait 20 seconds between each poll iteration.
  5. Check aws_devops_agent__get_task(task_id=TASK_ID) periodically — stop when terminal status (COMPLETED, FAILED, CANCELED, TIMED_OUT).

6. Present Results

Once the job reaches a terminal status:

  • If COMPLETED:
    1. Determine the report type from the test profile's agent type (UI or API). Call aws_devops_agent__get_release_ui_testing_report(execution_id=EXEC_ID) for UI profiles or aws_devops_agent__get_release_api_testing_report(execution_id=EXEC_ID) for API profiles.

    2. Write the report contents to a markdown file:

      release-testing-report-<YYYY-MM-DD-HHmmss>.md
    3. Inform the user that the report was saved, including the file path.

  • If FAILED or TIMED_OUT: Present the error information and suggest next steps.
  • If CANCELED: Inform the user the job was canceled and no report is available.

Cancelling a job

aws_devops_agent__cancel_release_testing_job(task_id=TASK_ID)

Error handling

  1. If the task status changes to FAILED, stop the workflow and report the error.
  2. If the task does not reach IN_PROGRESS within 5 minutes, cancel it using cancel_release_testing_job.
  3. If any output contains "NoCredentialsError", "ExpiredTokenException", or auth failures, suggest the user refresh their credentials or check the bearer token.
  4. If throttled (429 or ThrottlingException), wait 30 seconds before retrying. After 3 retries, inform the user.

Fallback (aws-mcp)

If the aws-devops-agent remote server is unavailable, use the AWS CLI directly:

Tell the user: "Remote server unavailable — using direct AWS API fallback."

1. Select Agent Space

List available agent spaces:

aws devops-agent list-agent-spaces --region us-east-1

Present the list to the user and ask which agent space they'd like to use. Do NOT proceed until the user has selected one. Use the selected agentSpaceId as SPACE_ID in all subsequent calls.

2. Start the Job

aws devops-agent create-backlog-task \
  --agent-space-id SPACE_ID \
  --task-type RELEASE_TESTING \
  --title 'Release Testing' \
  --priority MEDIUM \
  --description '{\"testProfileId\": \"<PROFILE_ID>\", \"webhookEventMessage\": \"<REQUIREMENT>\"}' \
  --region us-east-1

If the user provided a test requirement, include it as webhookEventMessage. If not, omit the field or leave it empty.

3. Poll for Status

aws devops-agent get-backlog-task \
  --agent-space-id SPACE_ID \
  --task-id TASK_ID \
  --region us-east-1

Poll every 30 seconds until the status transitions to IN_PROGRESS or a terminal state (COMPLETED, FAILED, CANCELED, TIMED_OUT).

4. Monitor Until Completion

Once IN_PROGRESS, poll for progress in a loop:

aws devops-agent list-journal-records \
  --agent-space-id SPACE_ID \
  --execution-id EXEC_ID \
  --order ASC \
  --region us-east-1
  1. Present each record to the user with a friendly progress update.
  2. Use next_token from the response to fetch only new records on subsequent polls.
  3. Wait 20 seconds between each poll iteration.
  4. Check get-backlog-task periodically — stop when terminal status (COMPLETED, FAILED, CANCELED, TIMED_OUT).

5. Present Results

Once the job reaches a terminal status:

  • If COMPLETED:
    1. Retrieve the report using the appropriate record type:

      • UI testing: --record-type qa_ui_testing_report
      • API testing: --record-type qa_api_testing_report
      aws devops-agent list-journal-records \
        --agent-space-id SPACE_ID \
        --execution-id EXEC_ID \
        --record-type qa_ui_testing_report \
        --order ASC \
        --region us-east-1
    2. Write the report contents to a markdown file:

      release-testing-report-<YYYY-MM-DD-HHmmss>.md
    3. Inform the user that the report was saved, including the file path.

  • If FAILED or TIMED_OUT: Present the error information and suggest next steps.
  • If CANCELED: Inform the user the job was canceled and no report is available.
Cancelling (fallback)
aws devops-agent update-backlog-task \
  --agent-space-id SPACE_ID \
  --task-id TASK_ID \
  --task-status CANCELED \
  --region us-east-1

Frequently asked questions

What does the Running Release Tests AI skill do?

Run automated release testing (UI or API) via the AWS DevOps Agent using a pre-configured test profile. Use when the user wants to validate multi-step workflows, verify features, check for regressions, or test API endpoints. Trigger words include run tests, UAT, test my app, test profile, UI test, API test, automated testing, regression test, QA, end-to-end test, run the QA agent.

Why use Running Release Tests on TypingMind?

Because you install it once and use it with any model. Running Release Tests is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Running Release Tests in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-agents-for-devsecops/skills/running-release-tests. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Running Release Tests?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Running Release Tests?

As many as you like. As long as a model supports skills, you can use Running Release Tests with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Running Release Tests AI skill free?

Yes. It is published on GitHub by aws under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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