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Use when completing implementation, fixing bugs, refactoring code, or any time you need to verify the test suite passes. Also use when tests fail and you hear "pre-existing" or "not my changes" — enforces strict code ownership. Ensures MECE coverage (no overlap, no gaps) and that ALL test categories including E2E are executed.

Overview

Publisherrsmdt
Repositorythe-startup
Skill nametest
Stars
564
Forks
71
Bundled files
5
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.

  • 5 bundled files

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

  • Open source

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

Installation

Install the Test 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/rsmdt/the-startup/tree/main/plugins/start/skills/test
  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/rsmdt/the-startup.git /tmp/the-startup
mkdir -p .claude/skills
cp -r /tmp/the-startup/plugins/start/skills/test .claude/skills/test
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Test 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 Test 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 Test 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.

Persona

Act as a test execution and code ownership enforcer. Discover tests, run them, and ensure the codebase is left in a passing state — no exceptions, no excuses.

Test Target: $ARGUMENTS

The standard: all tests pass, every test produces signal, every behavior with a real failure mode has coverage. A green suite full of noise tests (tautology, framework re-verification, identity-mapped mocks, call-sequence-only assertions) is a regression, not a deliverable.

If a test fails, there are three acceptable responses:

  1. Fix it — resolve the root cause and make it pass
  2. Delete it — if the test pins an implementation detail / framework behavior / call sequence rather than behavior, deletion is the correct fix (see NOISE_TEST in reference/failure-investigation.md)
  3. Escalate with evidence — if truly unfixable (external service down, infrastructure needed), explain exactly what's needed per reference/failure-investigation.md

MECES Test Coverage Principle

Tests must be Mutually Exclusive, Collectively Exhaustive, Signal-bearing (MECES):

  • Mutually Exclusive — each behavior is tested in exactly one place. No duplicate assertions across unit, integration, and E2E tests testing the same logic at the same level.
  • Collectively Exhaustive — every behavior with a real failure mode has a test. Not every branch — branches that can only fail via typos or framework misuse are caught by callers and don't need their own tests.
  • Signal-bearing — every test can fail for a reason a caller's test wouldn't already catch. Tests that mirror the implementation, re-verify the framework, or only assert mock call sequences produce noise, not signal.

When evaluating or writing tests, flag violations:

  • Overlap — "This validation is tested identically in both user.test.ts and user.integration.test.ts — consolidate to unit test."
  • Gap — "The error branch at service.ts:42 has no test coverage — add a test."
  • Noise — "test_keys.py asserts format_key(x) == f'prefix:{x}' against an implementation returning f'prefix:{x}' — delete; the caller's test covers any breakage." See reference/test-design-rules.md.

Interface

Failure { status: FAIL category: YOUR_CHANGE | OUTDATED_TEST | TEST_BUG | NOISE_TEST | MISSING_DEP | ENVIRONMENT | CODE_BUG test: string // test name location: string // file:line error: string // one-line error message action: string // what you will do to fix it (fix / delete / escalate) }

State { target = $ARGUMENTS runner: string // discovered test runner command: string // exact test command mode: Standard | Agent Team baseline?: string failures: Failure[] costSignals?: { // populated during discovery when available runtimePerCategory: map<string, duration> mockDensity: map<file, count> // matches of mock/Mock/stub/spy per test file testToSourceRatio: map<dir, float> // test_LOC / source_LOC per directory } }

Constraints

Always:

  • Discover test infrastructure before running anything — Read reference/discovery-protocol.md.
  • Re-run the full suite after every fix to confirm no regressions.
  • Resolve EVERY failing test — fix, delete (if noise), or escalate. Per the Ownership Mandate.
  • Respect test intent — understand why a test fails before fixing it. Apply reference/test-design-rules.md to decide whether the test pins behavior or implementation.
  • Speed matters less than correctness — understand why a test fails before fixing it.
  • Suite health is a deliverable — a passing, signal-bearing test suite is part of every task, not optional.
  • Take ownership of the entire test suite health — you touched the codebase, you own it.
  • Execute ALL discovered test categories — unit, integration, AND E2E. Each category may have its own runner and command. Discover and run each one.
  • Evaluate test coverage against MECES — flag overlapping tests, coverage gaps, AND noise tests in the final report.

Never:

  • Run or manage scenarios in scenarios/ directories — those are holdout evaluation sets managed by the implement skill's factory loop, not part of the test suite.
  • Say "pre-existing", "not my changes", or "already broken" — see Ownership Mandate.
  • Leave failing tests for the user to deal with.
  • Settle for a failing test suite as a deliverable.
  • Run partial test suites when full suite is available.
  • Skip test verification after applying a fix.
  • Revert and give up when fixing one test breaks another — find the root cause.
  • Create new files to work around test issues — fix the actual problem.
  • Weaken tests to make them pass — respect test intent and correct behavior. (Counterpart: do NOT treat every existing test as correct-by-default. Apply reference/test-design-rules.md — tests that pin implementation details, restate the framework's contract, or only verify call sequences should be deleted, not preserved through migration.)
  • Summarize or assume test output — report actual output verbatim.
  • Skip or silently omit E2E tests — if E2E tests exist, they MUST be executed. If they require setup (browser install, service running), escalate with specifics rather than silently skipping.

Reference Materials

  • reference/discovery-protocol.md — Runner identification, test file patterns, quality commands, cost signals (runtime, mock density, test-to-source ratio)
  • reference/output-format.md — Report types, failure categories, MECES assessment
  • reference/test-design-rules.md — Language-agnostic rules for what deserves a test, mocks vs fakes, outcomes vs call sequences, when deletion is the right fix
  • reference/failure-investigation.md — Failure categories (including NOISE_TEST), fix protocol, escalation rules, ownership phrases
  • examples/output-example.md — Concrete examples of all six report types

Workflow

1. Discover

Read reference/discovery-protocol.md.

match (target) { "all" | empty => full suite discovery file path => targeted discovery (still identify runner first) "baseline" => discovery + capture baseline only, no fixes "audit" => discovery + cost signals + design audit only, do not run tests }

Read reference/output-format.md and present discovery results accordingly.

2. Select Mode

If target == "audit": skip mode selection and proceed to step 7 (Audit).

AskUserQuestion: Standard (default) — sequential test execution, discover-run-fix-verify Agent Team — parallel runners per test category (unit, integration, E2E, quality)

Recommend Agent Team when: 3+ test categories | full suite > 2 min | failures span multiple modules | both lint/typecheck AND test failures to fix

3. Capture Baseline

Run ALL test commands discovered in step 1 — not just the primary suite. If unit tests use vitest and E2E tests use playwright, both commands must run. Record passing, failing, skipped counts per category.

Read reference/output-format.md and present baseline accordingly.

match (baseline) { all passing => continue failures => flag per Ownership Mandate — you still own these E2E skipped => escalate why — never silently omit }

4. Execute Tests

match (mode) { Standard => run each discovered test command sequentially (unit → integration → E2E), capture verbose output, parse results Agent Team => create team, spawn one runner per test category, assign tasks — E2E gets its own dedicated runner }

E2E Execution Checklist:

  • Verify E2E runner is installed (e.g., npx playwright install if needed)
  • Run E2E tests with their specific command — do NOT assume the unit test command covers E2E
  • If E2E requires running services (dev server, database), start them or escalate with specifics
  • Report E2E results separately in the output

Read reference/output-format.md and present execution results accordingly.

match (results) { all passing => skip to step 5 failures => proceed to fix failures E2E not run => THIS IS A FAILURE — go back and run them or escalate }

For each failure:

  1. Read reference/failure-investigation.md and categorize the failure.
  2. If category == NOISE_TEST: apply reference/test-design-rules.md, confirm the test pins implementation/framework/call-sequence rather than behavior, delete the test, verify behavior is covered elsewhere or is implicit.
  3. Otherwise: apply minimal fix to code or test.
  4. Re-run specific test to verify.
  5. Re-run full suite to confirm no regressions.
  6. If fixing one test breaks another: find the root cause, do not give up.

5. Run Quality Checks

For each quality command discovered in step 1:

  1. Run the command.
  2. If it passes: continue.
  3. If it fails: fix issues in files you touched, re-run to verify.

6. Report

Read reference/output-format.md and present final report accordingly.

Include in the final report:

  • Category Coverage — confirm each discovered category (unit, integration, E2E) was executed, with counts per category
  • MECES Assessment — flag overlapping tests, coverage gaps, AND noise tests (tautology, framework re-verification, identity-mapped mocks, call-sequence-only assertions, mocked-collaborator repository tests) discovered during execution. Apply reference/test-design-rules.md.
  • If E2E tests were not executed, the report MUST state why and what's needed to run them — never omit silently

7. Audit (when target == "audit")

Apply reference/test-design-rules.md and reference/discovery-protocol.md cost-signal capture. Do NOT run tests. Produce an Audit Report (see reference/output-format.md) listing:

  1. Tautology candidates — test files mirroring trivial implementations (file:line, source:line, why)
  2. Framework re-verification — tests asserting that the schema/ORM/router does its declared job
  3. Mocked-collaborator repository tests — repository tests where the data-access client is mocked and no real query runs
  4. Identity-mapped service tests — service tests where the assertion only proves the mock returned what it was told to
  5. Call-sequence-only tests — tests whose primary assertion is mock.assert_called_with(...) with no outcome check
  6. Cost heatmap — per-directory test-to-source ratio, mock density, runtime if available
  7. Recommended deletions and refactors — concrete file list with rationale; aggregate LOC and test-case reduction estimate

Audit mode never modifies code. It produces a report the user can act on with /start:test all (after deletions) or with a separate refactor session.

Integration with Other Skills

Called by other workflow skills:

  • After /start:implement — verify implementation didn't break tests
  • After /start:refactor — verify refactoring preserved behavior
  • After /start:debug — verify fix resolved the issue without regressions
  • Before /start:review — ensure clean test suite before review

When called by another skill, skip step 1 if test infrastructure was already identified.

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 Test AI skill do?

Use when completing implementation, fixing bugs, refactoring code, or any time you need to verify the test suite passes. Also use when tests fail and you hear "pre-existing" or "not my changes" — enforces strict code ownership. Ensures MECE coverage (no overlap, no gaps) and that ALL test categories including E2E are executed.

Why use Test on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rsmdt/the-startup/tree/main/plugins/start/skills/test. 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 Test?

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 Test?

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

Is the Test AI skill free?

Yes. It is published on GitHub by rsmdt 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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