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Agent Qa Authoring

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sickn33
agent-qa-authoring

Create, edit, validate, and run Agent QA tests, suites, and hooks through MCP or CLI while preserving canonical IDs and schema contracts.

Overview

Publishersickn33
Repositoryagentic-awesome-skills
Skill nameagent-qa-authoring
Stars
46.5K
Forks
6.8K
Bundled files
1
LicenseFSL-1.1-ALv2
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by sickn33 on GitHub. Read the source before you install it.

Installation

Install the Agent Qa Authoring 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/sickn33/agentic-awesome-skills.git /tmp/agentic-awesome-skills
mkdir -p .claude/skills
cp -r /tmp/agentic-awesome-skills/plugins/agentic-awesome-skills-claude/skills/agent-qa-authoring .claude/skills/agent-qa-authoring
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Qa Authoring 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 Agent Qa Authoring 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 Agent Qa Authoring 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.

Agent QA Authoring

Overview

Author Agent QA tests, suites, and hooks without inventing schema fields or identifiers. Prefer Agent QA's MCP tools, use the bundled contract reference for exact fields, and validate every definition before saving or running it.

When to Use

  • Creating or editing an Agent QA test, suite, or hook.
  • Validating Agent QA YAML or canonical IDs.
  • Running a newly authored Agent QA definition through MCP or CLI.
  • Investigating which Agent QA configuration fields or workspace patterns apply.

Preconditions and Approval Boundary

  • Work only in a configured Agent QA workspace that the user has authorized.
  • Inspect the requested scope before any create, update, delete, or test-run operation.
  • Obtain explicit confirmation before deleting a definition or running a test that can change external application state.
  • Keep credentials out of definitions and output; use the workspace's configured secret handling.

Workflow

  1. Discover the local surface with agent_qa_discover.
  2. Inspect active config with agent_qa_get_config, especially targets, devices, providers, and services.mcp.
  3. Load references/agent-qa-contracts.json when exact schema fields or ID contracts are needed.
  4. Generate every new ID with Agent QA tooling:
    • MCP: agent_qa_generate_id
    • CLI fallback: agent-qa ids generate <test|suite|hook|run|observation>
    • If neither surface is already installed, stop and ask the user to approve an exact Agent QA installation. Do not fetch and execute the package at runtime through npx or another moving package reference.
  5. Never hand-write IDs. Validate existing IDs with agent_qa_validate_id or agent-qa ids validate <type> <id> --json.
  6. Validate definitions before saving:
    • Tests: agent_qa_validate_test or agent_qa_validate_definition with kind: "test"
    • Suites: agent_qa_validate_suite or agent_qa_validate_definition with kind: "suite"
    • Hooks: agent_qa_validate_definition with kind: "hooks"
  7. Prefer MCP authoring mutations:
    • Tests: agent_qa_create_test, agent_qa_update_test, agent_qa_delete_test
    • Suites: agent_qa_create_suite, agent_qa_update_suite, agent_qa_delete_suite
    • Hooks: agent_qa_create_hook, agent_qa_update_hook, agent_qa_delete_hook
  8. Use CLI or YAML fallback only when MCP is unavailable. Keep file paths matched by workspace.testMatch or workspace.suiteMatch.

Required ID Contracts

  • Test IDs: t_ plus 10 id-agent words.
  • Suite IDs: s_ plus 10 id-agent words.
  • Hook IDs: h_ plus 10 id-agent words.
  • Run IDs: r_ plus 10 id-agent words.
  • Observation IDs: obs_ plus 10 id-agent words.

Before Running

  • Validate YAML first.
  • Prefer agent_qa_enqueue_test_run and agent_qa_enqueue_suite_run over shelling out.
  • If using the CLI fallback, run only after validation succeeds.
  • Reconfirm the target and environment when a test may mutate real data or trigger external actions.

Example

text
User: Add an Agent QA checkout test for the staging target and validate it, but do not run it yet.

Expected handling: discover the workspace, inspect the staging target, generate the test ID,
create the smallest valid definition, validate it, and stop before enqueueing a run.

Limitations

  • Requires an installed and configured Agent QA workspace plus any browser, mobile, model-provider, or application dependencies used by the selected target.
  • Does not infer undocumented config keys, selectors, UI states, credentials, or test data.
  • MCP availability and permissions vary by workspace; state which CLI or YAML fallback was used.
  • Validation proves schema compatibility, not that the application behavior or external environment is safe to exercise.

Do Not

  • Do not invent config keys or use legacy root config buckets.
  • Do not hand-write IDs.
  • Do not mutate files outside configured workspace patterns.
  • Do not run destructive or production-facing scenarios without the user's explicit scope and confirmation.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Agent Qa Authoring AI skill do?

Create, edit, validate, and run Agent QA tests, suites, and hooks through MCP or CLI while preserving canonical IDs and schema contracts.

Why use Agent Qa Authoring on TypingMind?

Because you install it once and use it with any model. Agent Qa Authoring 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 Agent Qa Authoring in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sickn33/agentic-awesome-skills/tree/main/plugins/agentic-awesome-skills-claude/skills/agent-qa-authoring. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Agent Qa Authoring?

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 Agent Qa Authoring?

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

Is the Agent Qa Authoring AI skill free?

Yes. It is published on GitHub by sickn33 under the FSL-1.1-ALv2 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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