NOASSERTION license. Self-improving QA harness with execution memory for natural-language web/mobile tests; connects to coding agents such as DeepSeek Harness via MCP tools and skills (dsh not explicitly mentioned in README).
DSH integration
Compatible
Author-claimed
Safety audit
Unaudited
Last verified
2026-08-21
License
NOASSERTION
01What can it help you accomplish?
Author natural-language regression tests for web and mobile apps and run them from an agent-driven workflow
Self-healing test runs that recover from UI drift and flaky interactions, plus execution memory that improves future runs and catches regressions before shipping
QA engineers and software teams that want to write tests in plain language instead of brittle selectors
Wire environment setup, API calls, fixture seeding and teardown into test runs via sandboxed hooks
Node, Bun, Python or Bash hooks executed in isolated Docker containers, with structured outputs passed back into the active test run
Teams that need scripted environment or data preparation around UI tests
02How to install into DeepSeek Harness
Prerequisites
- Node.js project with npm — agent-qa is installed as a dev dependency via `npm install -D agent-qa`
- Docker installed before using hooks — Docker is required for the Node, Bun, Python and Bash hook containers
- Optional: `@vostride/agent-qa-subscription-auth` for Codex or Claude Code subscription auth
Installation steps
- 01
`npm install -D agent-qa`
$ npm install -D agent-qa
- 02
Optional (Codex or Claude Code subscription auth): `npm install -D @vostride/agent-qa-subscription-auth`
$ npm install -D @vostride/agent-qa-subscription-auth
- 03
`npx agent-qa init`
$ npx agent-qa init
- 04
`npx agent-qa install-browsers --chromium`
$ npx agent-qa install-browsers --chromium
- 05
Mobile projects: `npx agent-qa install-mobile-drivers --all`
$ npx agent-qa install-mobile-drivers --all
- 06
`npx agent-qa dashboard --open` — start the dashboard, complete auth, and run tests from the UI
$ npx agent-qa dashboard --open
Verify the integration
Not specified by the author
03DSH integration and capability boundaries
Exposes MCP and skills for coding agents (per README); DeepSeek Harness/dsh is not mentioned in the README, so usage inside dsh is inferred via MCP
Natural-language tests for web and mobile
test definitions written in human language (actions and assertions)→agents execute tests from visible roles, labels, and screen state
launches installed browsers / mobile drivers to execute test runssends test context to the LLM endpoint you configureSelf-healing execution with memory
failing sub-actions (click, fill, select) and past-run observations→re-observed UI and alternate paths within the same run; execution memory added to future runs
persists execution memory built from product, suite, and test observations for future runsSandboxed test hooks
Node, Bun, Python or Bash hook scripts→hooks run in isolated Docker containers; structured outputs passed back into the active run
runs Docker containers for hooks (Docker required)Bring your own LLM + dashboard/CLI/MCP
any OpenAI-/Anthropic-compatible endpoint, Gemini, local or open-source model, or Codex / Claude Code subscription→tests executed with the model of your choice; dashboard and CLI for humans, MCP and skills for coding agents
04Who is it for? When not to use it?
Good for
- QA engineers and software teams that want to write tests in plain language instead of brittle selectors
- Teams that need scripted environment or data preparation around UI tests
Not for
- Hooks require Docker — agent-qa runs Node, Bun, Python and Bash hooks in isolated Docker containers, so Docker must be installed before using hooks.
- The README never mentions DeepSeek Harness or dsh; running agent-qa inside dsh is inferred from the stated MCP and skills support for coding agents, not documented by the project.
05Compatibility, maintenance and safety notes
- Hooks require Docker — agent-qa runs Node, Bun, Python and Bash hooks in isolated Docker containers, so Docker must be installed before using hooks.
- No bundled model — you must bring your own LLM via OpenAI-/Anthropic-compatible endpoints, Gemini, local or open-source models, or Codex / Claude Code subscriptions, which means network access and your own credentials/subscription.
- The README never mentions DeepSeek Harness or dsh; running agent-qa inside dsh is inferred from the stated MCP and skills support for coding agents, not documented by the project.
NOASSERTION · actively maintained (last push 2026-08-03)
06Frequently asked questions
Does agent-qa officially support DeepSeek Harness?
The README does not mention DeepSeek Harness or dsh. agent-qa ships MCP and skills for coding agents and supports bring-your-own LLM, so it can be used alongside dsh as an MCP-based QA tool — but that integration is not documented by the project.
How do I install agent-qa?
Run `npm install -D agent-qa`, then `npx agent-qa init` and install runtime support such as `npx agent-qa install-browsers --chromium` (mobile projects: `install-mobile-drivers --all`). Start the dashboard with `npx agent-qa dashboard --open`. For Codex or Claude Code subscription auth, also install `@vostride/agent-qa-subscription-auth`.
Is Docker required?
Only if you use hooks — agent-qa runs Node, Bun, Python and Bash hooks in isolated Docker containers, and Docker must be installed before using them.
Which LLMs can run the tests?
Any model via OpenAI- or Anthropic-compatible endpoints, Gemini, local or open-source models, or subscriptions like Codex and Claude Code.
Where do tests and memory live?
Tests, configs, hooks, memory and suite logic all live as version-controlled code in your repo, so every change can be diffed, reviewed, reused and shared across teams.
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08Data and sources
**Built for humans and machines**: A polished dashboard and CLI for developers, plus MCP and skills for coding agents.
This page is generated from the project’s public documentation, repository metadata and a structured parse of DSH Plugins; last verified on 2026-08-21. Found an error? Submit a correction.
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