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ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.

Quality

76%

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tessl review fix ./skills/ai-regression-testing/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%Weight 40%Scale 1-5

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

A highly actionable, workflow-driven skill with copy-paste-ready test infrastructure and an explicit validation-gated bug-check sequence. Its weaknesses are over-explanation of programming fundamentals Claude already knows (error-state cleanup, optimistic rollback) and a monolithic single-file layout where a pattern catalog and test boilerplate could be split into reference files.

Suggestions

Trim or remove Pattern 3 (error state leakage) and Pattern 4 (optimistic rollback) — both are standard programming knowledge — and keep only the genuinely AI-specific patterns (sandbox/production mismatch, SELECT clause omission).

Move the test helper boilerplate (vitest.config.ts, setup.ts, helpers.ts) and the full pattern catalog into a references/ file, keeping SKILL.md as a lean overview with clearly signaled one-level-deep links.

Condense the four-step "Real-world example" narrative into a one-line summary of the lesson (sandbox/production inconsistency is the #1 AI regression) to save tokens.

DimensionReasoningScore

Conciseness

The novel material (sandbox setup, test helper, bug-check command) is efficient, but Pattern 3 (clearing state on error) and Pattern 4 (optimistic-update rollback) explain standard programming knowledge Claude already has, and the multi-step "Real-world example" narrative is story padding — more than the "minor instances" of anchor 4, so anchor 3 fits best.

3 / 5

Actionability

Fully executable, copy-paste-ready guidance: complete vitest.config.ts, setup.ts, a reusable createTestRequest/parseResponse helper, full regression test examples, and a concrete .claude/commands/bug-check.md definition covering the common cases — matching anchor 5.

5 / 5

Workflow Clarity

The bug-check workflow is clearly sequenced with explicit validation gates ("If tests fail → report as highest priority bug", "Only proceed to Step 2 if both pass") and a feedback loop ("For each fix, write a regression test → Next bug-check catches if fix breaks") — matching anchor 5. No destructive/batch cap applies.

5 / 5

Progressive Disclosure

The body is well-sectioned with clear headers, but at ~380 lines everything is inlined with no bundle files — a pattern catalog and test boilerplate that could live in references/ sit inline in SKILL.md, and the under-50-line simple-skill exception does not apply — anchor 3.

3 / 5

Total

16

/

20

Passed

Description

66%Weight 40%Scale 1-5

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

A specific, third-person description that clearly names its niche (AI-assisted development regression testing) with several concrete capabilities and good trigger keywords. Its main gap is the absence of any explicit "Use when..." trigger clause, which weakens the when-to-activate guidance and caps completeness.

Suggestions

Add an explicit trigger clause, e.g. "Use when an AI agent (Claude Code, Cursor, Codex) has modified API routes or backend logic, after a bug fix, or when running a bug-check/review on AI-generated code."

Include the tool names users actually say (Claude Code, Cursor, Copilot, vitest) as trigger terms to improve keyword coverage and distinctiveness against general testing skills.

DimensionReasoningScore

Specificity

"Sandbox-mode API testing without database dependencies" and "automated bug-check workflows" are concrete, specific actions, but "patterns to catch AI blind spots" is abstract, leaving minor gaps in coverage — matching anchor 4 rather than the comprehensive coverage of anchor 5.

4 / 5

Completeness

The "what" is clear (regression testing strategies, sandbox-mode API testing, automated bug-check workflows), but there is no "Use when..." clause or equivalent explicit trigger guidance — the "when" is only weakly implied by context, which caps completeness at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Natural terms like "regression testing", "bug-check", "sandbox", and "AI-assisted development" give good keyword coverage, but common variations users would actually say (e.g. "Claude Code", "Cursor", "write tests", "vitest") are missing — above anchor 3's partial coverage, short of anchor 5's synonym-and-extension completeness.

4 / 5

Distinctiveness Conflict Risk

The framing "where the same model writes and reviews code" carves a distinct AI-specific testing niche with low conflict risk against general testing skills, though minor overlap with generic regression-testing skills remains — anchor 4 rather than the fully distinct anchor 5.

4 / 5

Total

15

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

valeriibeck-star/claude-skills

Path

skills/ai-regression-testing/SKILL.md

Reviewed

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