follow-test-patterns

Included with Lifetime

$97 forever

Use when writing tests to ensure they follow project conventions. References patterns from thoughts/notes/testing.md.

Writing & Docs

What this skill does


# Follow Test Patterns

Reference discovered test patterns when writing tests to ensure consistency with project conventions.

## When to Use

- Before writing any test file
- When implementing test-related phases in plans
- When user asks you to add tests

## Workflow

### 1. Check for Pattern Document
```bash
if [ -f thoughts/notes/testing.md ]; then
  # Read and follow patterns
else
  # Prompt user to run discover-test-patterns first
  echo "No test patterns found. Run discover-test-patterns skill first."
fi
```

### 2. Read Pattern Document

Read `thoughts/notes/testing.md` fully to understand:
- File naming conventions
- Testing framework and imports
- Test structure (table-driven, etc.)
- Assertion style
- Mocking approach

### 3. Apply Patterns to New Tests

Use the discovered patterns for:

**File Naming**:
- Follow the pattern (e.g., `*_test.go`, `*.test.ts`)
- Place alongside source or in test directory as per convention

**Imports**:
- Use same testing framework (testify, jest, pytest)
- Import same assertion libraries

**Test Structure**:
- If codebase uses table-driven tests, use that pattern
- If codebase uses describe/it blocks, use that pattern
- Match indentation and formatting

**Assertions**:
- Use same assertion style (require.Equal vs assert.Equal)
- Follow error message conventions

**Mocking**:
- Use same mocking library (mockery, jest.mock, unittest.mock)
- Follow interface/class mocking patterns found in codebase

## Alternative: Use Test-Writer Agent

For complex test generation, spawn the test-writer agent:

```markdown
Task(subagent_type="workflows:test-writer",
     prompt="Generate tests for [functions] following patterns in testing.md.
     Expected behavior: [describe].
     Return test code only.")
```

**Benefits**:
- Conserves main agent context (3k instead of 20k+)
- Agent reads testing.md and examples in isolation
- Returns only the test code you need
- Follows project patterns automatically

**When to use**:
- Generating multiple test files
- Complex table-driven tests
- During phased implementation (see `spawn-implementation-agents`)

### 4. Verify Consistency

After writing tests, verify:
- File name matches convention
- Framework imports are correct
- Test structure matches examples
- Assertions use same style
- Tests are in correct location

## Example

If `thoughts/notes/testing.md` shows:
```
## Go Test Patterns
- File: `*_test.go` alongside source
- Framework: testify/require
- Pattern: Table-driven tests
```

Then write:
```go
package handlers

import (
    "testing"
    "github.com/stretchr/testify/require"
)

func TestNewFeature(t *testing.T) {
    tests := []struct {
        name string
        input FeatureInput
        want FeatureOutput
    }{
        {name: "valid case", input: ..., want: ...},
    }
    for _, tt := range tests {
        t.Run(tt.name, func(t *testing.T) {
            got := NewFeature(tt.input)
            require.Equal(t, tt.want, got)
        })
    }
}
```

## Benefits

- Tests automatically match project style
- Reduces review feedback
- Faster test writing with clear examples
- Consistency across all new tests

Files: 1

Size: 3.2 KB

Complexity: 6/100

Category: Writing & Docs

Source: https://github.com/eveld/claude/tree/main/skills/follow-test-patterns

Related in Writing & Docs

jax-development

Included

Use this skill when the user is writing, debugging, profiling, refactoring, reviewing, benchmarking, parallelising, exporting, or explaining JAX code, or when they mention JAX, jax.numpy, jit, grad, value_and_grad, vmap, scan, lax, random keys, pytrees, jax.Array, sharding, Mesh, PartitionSpec, NamedSharding, pmap, shard_map, Pallas, XLA, StableHLO, checkify, profiler, or the JAX repo. It helps turn NumPy or PyTorch-style code into pure functional JAX, fix tracer/control-flow/shape/PRNG bugs, remove recompiles and host-device syncs, choose transforms and sharding strategies, inspect jaxpr/lowering/IR, and benchmark compiled code correctly.

Writing & Docsscripts

nature-article-writer

Included

Drafts, rewrites, diagnostically critiques, and style-calibrates primary research manuscripts for Nature and Nature Portfolio journals. Use when the user wants a Nature-style title, summary paragraph or abstract, introduction, results, discussion, methods, figure legends, presubmission enquiry, cover letter, reviewer response, or when a scientific draft sounds generic, jargon-heavy, structurally weak, or AI-ish and needs precise, broad-reader-friendly prose without inventing data, analyses, or references. Best for primary research articles and letters rather than reviews or press releases unless explicitly adapting one.

Writing & Docsscripts

deckrd

Included

Document-driven framework that derives requirements, specifications, implementation plans, and executable tasks from goals through structured AI dialogue. Use when user says "write requirements", "create spec", "plan implementation", "derive tasks", "structure this feature", "break down into tasks", or "document this module". Also use for reverse engineering existing code into docs (/deckrd rev). Do NOT use for direct code writing — use /deckrd-coder after tasks are generated. Do NOT use when the user only wants to run or fix existing code without planning.

Writing & Docsscripts

clinical-decision-support

Included

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

Writing & Docsscripts

handling-sf-data

Included

Salesforce data operations with 130-point scoring. Use this skill to create, update, delete, bulk import/export, generate test data, and clean up org records using sf CLI and anonymous Apex. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, needs data factory patterns for Apex tests, or needs to seed/clean records in a Salesforce org. DO NOT TRIGGER when: SOQL query writing only (use querying-soql), Apex test execution (use running-apex-tests), or metadata deployment (use deploying-metadata).

Writing & Docsscripts

accelint-ac-to-playwright

Included

Convert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.

Writing & Docsscripts