BB tailwind-patterns
Tailwind CSS v4 principles. CSS-first configuration, container queries, modern patterns, design token architecture.
Claims to teach AI the Tailwind CSS v4 way: CSS-first setup, container queries, design tokens. Reality: one file with 1759 tokens, no scripts or code samples. Tests found no critical issues, quality score 81, but process score sits at 67. Works across all major platforms.
For quick prototyping in Cursor or Claude Code it'll serve as a cheat sheet on syntax. Don't expect it to grasp token architecture deeply—it's reference material, not a mentor. Install if you need a v4 reminder, not a comprehensive guide.
Tailwind CSS v4 principles.
As a process B 67/100 · Nearly there — weak spots: result and completion, when it triggers, failures and branches
The same skill appears in 1 more place: agentic-awesome-skills
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 · 0
✓ No critical or high findings
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
edit-residuethe text marks something as outdated (lines 15, 167): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 67/100
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Result and completion. Does not say what the result is
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 6 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1759 tokens
- 100Running it twice. No mutating operations
- low 14 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 115: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 36 headings
- +3Step-by-step instructions: 6 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.