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platform-testing

Framework-agnostic testing principles — test philosophy, structure, mocking boundaries. Use when writing, reviewing, or debugging tests.

Install with Tessl CLI

npx tessl i github:ravnhq/ai-toolkit --skill platform-testing
What are skills?

66

1.18x

Quality

51%

Does it follow best practices?

Impact

94%

1.18x

Average score across 3 eval scenarios

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/platform/platform-testing/SKILL.md
SKILL.md
Review
Evals

Principles

  • Test behavior, not implementation details
  • Prefer integration tests over unit tests (Testing Trophy)
  • Arrange-Act-Assert (AAA) pattern in every test
  • Tests must be independent — no shared mutable state
  • Keep tests small and focused — one behavior per test
  • Name tests to describe the behavior being verified
  • Optimize for confidence, not coverage percentage
  • Don't chase 100% coverage — test what matters

Rules

See rules index for detailed patterns.

Examples

Positive Trigger

User: "Define integration-vs-unit test boundaries and mocking strategy."

Expected behavior: Use platform-testing guidance, follow its workflow, and return actionable output.

Non-Trigger

User: "Create a tRPC router for billing procedures."

Expected behavior: Do not prioritize platform-testing; choose a more relevant skill or proceed without it.

Troubleshooting

Skill Does Not Trigger

  • Error: The skill is not selected when expected.
  • Cause: Request wording does not clearly match the description trigger conditions.
  • Solution: Rephrase with explicit domain/task keywords from the description and retry.

Guidance Conflicts With Another Skill

  • Error: Instructions from multiple skills conflict in one task.
  • Cause: Overlapping scope across loaded skills.
  • Solution: State which skill is authoritative for the current step and apply that workflow first.

Output Is Too Generic

  • Error: Result lacks concrete, actionable detail.
  • Cause: Task input omitted context, constraints, or target format.
  • Solution: Add specific constraints (environment, scope, format, success criteria) and rerun.

Workflow

  1. Identify whether the request clearly matches platform-testing scope and triggers.
  2. Apply the skill rules and referenced guidance to produce a concrete result.
  3. Validate output quality against constraints; if gaps remain, refine once with explicit assumptions.
Repository
ravnhq/ai-toolkit
Last updated
Created

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.