integration-test-generator

Generate integration tests for multiple interacting components in Python. Use when testing interactions between: (1) Multiple services or APIs (REST/GraphQL endpoints, microservices), (2) Database operations with repositories/ORMs (SQLAlchemy, Django ORM), (3) External services (payment gateways, email services, third-party APIs), (4) Message queues and event-driven systems, (5) Full stack workflows (API + database + business logic). Provides test structure templates, fixtures, test data builders, and patterns for pytest-based integration testing.

1.02x

Quality

86%

Does it follow best practices?

Impact

91%

1.02x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Quality

Content

72%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a solid integration test skill with excellent actionability - all code examples are executable and cover common patterns well. The main weaknesses are some verbosity in introductory sections and missing validation/verification steps in workflows involving database operations. The progressive disclosure is well-handled with clear references to detailed documentation.

Suggestions

Remove the 'When to Use Integration Tests' section - this information is already in the skill description and Claude understands integration testing concepts

Add explicit validation checkpoints to database integration examples (e.g., verify transaction committed, check for orphaned records after teardown)

Trim explanatory comments in code examples that state the obvious (e.g., '# Test runs here' after yield)

Dimension	Reasoning	Score
Conciseness	The skill includes some unnecessary explanations (e.g., 'Integration tests verify that multiple components work correctly together' is obvious to Claude). The content is generally useful but could be tightened - the 'When to Use Integration Tests' section restates what's in the description.	2 / 3
Actionability	Provides fully executable, copy-paste ready code examples throughout. All patterns include complete Python code with imports, fixtures, and assertions. The pytest commands section gives concrete CLI examples.	3 / 3
Workflow Clarity	The 'test_complete_checkout_workflow' example shows a clear sequence, but most examples lack explicit validation checkpoints. For integration tests involving database operations, there's no guidance on verifying test isolation or handling rollback failures.	2 / 3
Progressive Disclosure	Well-structured with clear sections progressing from basic to advanced. References to external files (patterns.md, test_data.md) are clearly signaled and one level deep. Quick Reference section provides scannable summary.	3 / 3
	Total	10 / 12 Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is an excellent skill description that hits all the marks. It uses proper third-person voice, provides specific concrete actions with named technologies, includes comprehensive trigger terms developers would naturally use, and has an explicit 'Use when' clause with detailed scenarios. The numbered list format makes the scope crystal clear and distinguishes it from related testing skills.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'Generate integration tests', 'test structure templates, fixtures, test data builders, and patterns' with explicit technologies (SQLAlchemy, Django ORM, pytest) and specific domains (REST/GraphQL endpoints, microservices, payment gateways).	3 / 3
Completeness	Clearly answers both what ('Generate integration tests... Provides test structure templates, fixtures, test data builders, and patterns') AND when ('Use when testing interactions between...' with five explicit numbered scenarios). The 'Use when' clause is explicit and comprehensive.	3 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'integration tests', 'APIs', 'REST', 'GraphQL', 'microservices', 'database', 'SQLAlchemy', 'Django ORM', 'payment gateways', 'message queues', 'pytest', 'fixtures'. These are terms developers naturally use when seeking integration testing help.	3 / 3
Distinctiveness Conflict Risk	Clear niche focused specifically on Python integration testing with explicit scope (multiple interacting components, specific frameworks). The numbered list of scenarios and Python/pytest focus distinguishes it from general testing skills or unit testing skills.	3 / 3
	Total	12 / 12 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: ArabelaTso/Skills-4-SE
Commit: 0f00a4f

Reviewed: 4 months ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.