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test-audit

Audit a test suite to identify redundant tests, empty checks, and tests tied to internal implementation. Consolidate or remove them with evidence while preserving useful checks that detect regressions, meaning previously fixed problems returning.

OriginalShow the original description

Garden the test suite by finding and removing redundant, vacuous, or implementation-coupled tests while preserving useful regression coverage. Use for test audits, test pruning, duplicate coverage, or reducing CI test cost. Supports focused cleanups and coordinated audit campaigns.

AI rating100/ 100See how to install

Good for

  • Audit duplicate test coverage
  • Prune tests while preserving regression detection
  • Review tests tied to internal implementation
  • Assess test execution and maintenance costs

Overview

What it does

Examines test suites for duplication, checks that verify nothing meaningful, and tests closely tied to internal implementation. For each removal candidate, it identifies the problem the test detects and which retained test will cover it. Unique checks move first, followed by decisions to consolidate, repair, delete, retain, or defer. It supports focused cleanups and audits spanning multiple owners or PRs.

When it helps

Useful for development teams reviewing the effort spent running and maintaining tests. When similar tests accumulate, or behavior-preserving code changes frequently break tests, it helps establish evidence for what to keep. Retaining tests after investigation is also a valid outcome.

Example requests

  • “Find duplication in this test suite and explain what to keep and what could be removed.”
  • “Clean up these tests while preserving regression detection, then validate with related tests.”

Notes

Similarity, size, slowness, or suspected AI authorship alone do not justify deletion. Check the baseline before changes and validate retained and related tests. Cost reports distinguish measured, estimated, and historical evidence; cleanup alone does not establish a speedup. Publishing or merging stays within the request's authorization.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodIt explicitly targets test audits and duplicate cleanup while preserving regression detection.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodIt provides four removal questions, a six-step workflow, and required completion report contents.
SafetyAre sending data, deleting files, and running commands disclosed?
AGoodIt requires evidence and moving unique checks before deletion, validation afterward, and authorization for publishing or merging.
Easy setupDoes it need few tools or API keys, and are they documented?
AGoodIt states that it is self-contained and links to audit, validation, and repository-specific guidance.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 20, 2026. Treat it as a guide and read the original before installing.

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Files included (7)

  • SKILL.md4.2 KB
  • agents/openai.yaml266 B
  • CAMPAIGN.md5.4 KB
  • NOTICE.md1.6 KB
  • references/audit.md4.8 KB
  • references/paperclip.md3.9 KB
  • references/validation.md5.1 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Test Audit

Reduce execution and maintenance cost while preserving meaningful failure detection. Investigate aggressively; delete only with evidence. Retaining an area after review is a valid result. This skill is self-contained; upstream attribution is in NOTICE.md.

Choose the scope

Decision gate

For every proposed removal, answer:

  1. Which observable contract and plausible regression do the assertions cover?
  2. Which retained file/case detects that regression through the responsible production code? Otherwise, why is the assertion vacuous or contract retired?
  3. Does this candidate uniquely cover a transport, permission, lifecycle, storage boundary, platform, default, or other independent failure mode?
  4. What improves: executions, fixtures, processes, maintenance, or runtime?

Prefer the smallest test that reaches the code responsible for the contract. A broader suite is not automatically stronger proof. Similarity, size, slowness, or suspected AI authorship alone never justify deletion.

Prevent new duplication

Apply this gate to tests added or changed during gardening:

  • Name the regression that existing proof misses. Extend an appropriate owner or table before adding another suite; another layer needs a distinct risk.
  • Exercise the responsible production behavior. Do not add a mock that supplies the result being asserted or a production hook solely for convenient testing.
  • Check observable outcomes that survive behavior-preserving refactors. A negative case must reach its named guard with otherwise valid inputs.

Focused workflow

  1. Inspect: pin the base; read candidates, keepers, fixtures, production callers, history, and CI routing. Preserve unrelated work.
  2. Plan: mark retain, repair, consolidate, delete, or defer. Name remaining proof and assertions to move; look for redundant suites as well as cases.
  3. Prove: establish the affected baseline locally or from matching-revision CI. Diagnose failures before treating them as cleanup candidates.
  4. Edit: move unique assertions first, then retire duplicates and unused support. Production-seam deletion needs its own caller/contract evidence.
  5. Validate: run keepers and affected siblings, verify selection, and apply the validation guide's intended-failure controls where needed.
  6. Review: reconcile deleted contracts with retained proof. Publish or merge only within the task's authorization.

Completion and reporting

Keep audit decisions, plans, ledgers, and validation evidence in the task and PR description. Do not create or modify repository documentation, including doc/plans/ audit receipts or reports, unless the human explicitly requests documentation changes. A test cleanup does not need a repository report.

Report removals and keepers, retained/deferred candidates, checks and limitations, distinct cases versus repeated executions, and test/support versus production LOC. Label cost evidence as measured, estimated, or historical; a proven simplification does not require a measurable speedup.

State the actual endpoint: findings, validated local patch, published PR, intermediate merge, or landed in the intended target. Stop at the requested scope/time limit or completed delivery, not a deletion quota. For another pass, refresh the base and prior findings; revisit retained tests only with new evidence.

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