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E2e Testing

Community
nahid-sparktales
e2e-testing

Build and keep end-to-end suites that are worth their runtime — which journeys belong at this level, selectors that survive refactors, waiting on state instead of sleeping, per-spec data isolation, and flake triage that finds the cause. Use when adding or repairing an e2e suite, when specs are slow or intermittently red, or when deciding whether a case belongs here at all. Not for one-off checking that a change renders, not for unit or integration tests, and not for load testing.

Overview

Publishernahid-sparktales
Repositoryagent-dispatcher
Skill namee2e-testing
Stars
58
Forks
5
Bundled files
1
LicenseMIT
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 nahid-sparktales on GitHub. Read the source before you install it.

Installation

Install the E2e Testing 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.
    https://github.com/nahid-sparktales/agent-dispatcher/tree/main/skills/quality/e2e-testing
  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/nahid-sparktales/agent-dispatcher.git /tmp/agent-dispatcher
mkdir -p .claude/skills
cp -r /tmp/agent-dispatcher/skills/quality/e2e-testing .claude/skills/e2e-testing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable E2e Testing 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 E2e Testing 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 E2e Testing 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.

End-to-end testing

The end-to-end level is the most expensive coverage available and the only level that can prove a journey holds together. Suites die when those two facts are confused: everything gets tested here, the suite gets slow and flaky, reruns become routine, and a red run stops meaning anything.

A suite whose failures are ignored is worse than no suite — it costs runtime and provides a false signal.

When this fires

Creating, extending, triaging or pruning an automated end-to-end suite. It does not fire for manually confirming that a change renders and works (browser-verification), nor for coverage that a unit or integration test could hold (test-design).

Procedure

  1. Admit a journey only if it loses its meaning at a lower level. Signup through first use; add to cart through payment confirmation; a permission boundary spanning UI, API and database. If a unit or integration test can observe the same failure, it belongs there — cheaper, faster, and it names the cause instead of the symptom. Validation-message wording, per-field rules and error formatting do not belong here.
  2. One spec is one journey with one reason to fail. A spec that walks six unrelated features tells you only that one of six broke, and it breaks six times as often.
  3. Set up state through the API or a fixture, and assert through the UI. Driving the UI to create preconditions triples the runtime and makes every spec fail whenever an unrelated screen changes. The journey under test is the part you click.
  4. Log in once, not per spec. Authenticate through an API call or a seeded session/storage state and reuse it. The login form itself is one spec's journey, not every spec's preamble.
  5. Give every spec its own data. A unique account, tenant or record per run, created by the spec and torn down or left disposable. Shared seed data makes specs order-dependent and turns parallel execution into cross-talk. Never rely on a record another spec created.
  6. Select by role and accessible name, or by a dedicated test id. In that order. CSS class chains, nth-child and user-visible copy all break on changes that break nothing real — and role-based selection tests something true about the page while it does it.
  7. Wait for states, never for durations. Wait for the element to be visible and enabled, for the request to settle, for the URL or the rendered text to change. Use the framework's retrying assertions with an explicit timeout. A fixed sleep is either slower than necessary or shorter than reality, usually both on the same day.
  8. Assert something a user could see. Text on the screen, the URL, a value in a field, an item that disappeared. Asserting on a network call or on internal state is an integration test wearing a browser.
  9. Pin the environment. A named build, seeded data, a fixed viewport, timezone and locale, and animations reduced. These are the four things that differ between a laptop and CI. Never point the suite at production — it creates real records, sends real mail and can touch real people; that is outward-facing, so stop and ask, and use a disposable environment instead.
  10. Capture the artifact on failure — trace, video, screenshot, console log, the failing selector. A failure with no artifact costs a full reproduction cycle; with one, triage is usually a minute.
  11. Allow at most one retry, and treat a pass-on-retry as a failure to investigate, not a pass. Record which specs needed a retry, because that record is the flake list.
  12. Triage each flake to a cause before touching it. Four causes, four different fixes: a race in the test (wait on the right state), a race in the application (a real bug — fix the app, not the wait), shared or leaked state (isolate), or an unstable dependency (stub it at the network boundary, or drop the journey). "Fixed" by adding a sleep is not fixed; it is a longer suite with the same defect.
  13. Prove stability before believing it. Run the suite twice back to back on the same build, and once with spec order shuffled or parallelism increased. Green once is not green.
  14. Prune on evidence. For a suite that hurts, measure: runtime per spec, failure history, how often a red run found a real defect. Quarantine anything unfixable with an owner and a date, and propose deletions with the numbers attached. Deleting specs removes someone's coverage — ask before removing them, and never quarantine as a way of silencing a real failure.

Checklist

  • Every spec is a journey that no lower level could observe
  • One journey per spec, one reason to fail
  • Preconditions created by API or fixture, not by clicking
  • Authentication seeded once and reused
  • Data unique per spec and per run; no cross-spec dependency
  • Selectors are role or test-id based, not classes, positions or copy
  • No fixed sleeps anywhere; every wait names a state
  • Assertions are on user-visible outcomes
  • Environment pinned: build, seed, viewport, timezone, locale, animations
  • Traces or screenshots retained on failure
  • Retries capped at one and every retry recorded
  • Suite run twice and shuffled before being called stable
  • Quarantine list has owners and dates; nothing silenced without one

Failure handling

  • Passes locally, fails in CI — compare the four usual suspects first: viewport, timezone and locale, animation and network timing, and parallel workers sharing data. Read the trace before changing the test.
  • Fails once, passes on rerun — that is a flake, not a pass. Log it and triage it to a cause. Reporting it as green is how a real race reaches production.
  • Suite is green but the feature is broken — the coverage is at the wrong level or the assertions are not user-visible. Say which, and fix the level rather than adding more specs.
  • A journey cannot be automated (third-party payment page, real email or SMS, a device capability) — stub at the network boundary if that keeps the journey meaningful, otherwise state plainly that this path is manually checked, by whom and when. Do not simulate it and call it covered.
  • Browser or runner unavailable — say the end-to-end level could not be run, name what was checked instead, and do not describe the journeys as passing.
  • Under pressure to skip a failing spec to unblock a release — that is a release decision, not a test change. Report what the spec covers and what shipping without it risks, and let the owner decide.

Evidence to report

The journeys covered and, explicitly, the ones that are not; the command that runs the suite with its real output; the result of two consecutive runs and one shuffled run; traces or screenshots for every failure; the retry and quarantine list with owners and dates; and the environment the suite ran against, named. A suite described as passing without a second run and an environment name is a single sample.

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 E2e Testing AI skill do?

Build and keep end-to-end suites that are worth their runtime — which journeys belong at this level, selectors that survive refactors, waiting on state instead of sleeping, per-spec data isolation, and flake triage that finds the cause. Use when adding or repairing an e2e suite, when specs are slow or intermittently red, or when deciding whether a case belongs here at all. Not for one-off checking that a change renders, not for unit or integration tests, and not for load testing.

Why use E2e Testing on TypingMind?

Because you install it once and use it with any model. E2e Testing 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 E2e Testing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nahid-sparktales/agent-dispatcher/tree/main/skills/quality/e2e-testing. 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 E2e Testing?

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 E2e Testing?

As many as you like. As long as a model supports skills, you can use E2e Testing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the E2e Testing AI skill free?

Yes. It is published on GitHub by nahid-sparktales under the MIT 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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