AB playwright-test-generator
AI-driven Playwright test code generator for QA engineers. Generates Page Object Models, standard test scripts, and data-driven tests from natural language descriptions, HTML analysis, or page URLs. Supports pytest-playwright, Jest Playwright, and native Playwright. Activate when the user asks to "generate Playwright tests", "create test script", "build POM from page", or mentions Playwright test generation.
As a process B 71/100 · Nearly there — weak spots: running it twice, progress reporting
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 5
✓ No critical or high findings
Medium and low: 5
-
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:286High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)"integrity": "sha5…ywo+qwL+oL8H…C1U+vRfLQDvw==",
quoted -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:302High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha512-Yqfm+XDx0+Prh3…1yC+JWZ2…IL7+vK+Clp7…D7g==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:315High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…xZl+RoGR…fbT/ZgrF…0EA==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:328High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…3bJ+V0If…IXN+CL65…a4w==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:344High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)"integrity": "sha5…H47+FFon…OsV/4+RRsz…0ig==",
quoted
Files scanned: 23. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 71/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 18 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1255 tokens
- low 12 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 411: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 18 items
- +3Output format is stated explicitly
- +4Has examples (7 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.