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AC shadcn

Manages shadcn/ui components and projects, providing context, documentation, and usage patterns for building modern design systems.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 11 files body ≈ 4 053 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Manages shadcn/ui components and projects, providing context, documentation, and usage patterns for building modern design systems.

As a process C 55/100 · Has gaps — weak spots: result and completion, failures and branches, progress reporting

ProcedureWriting and documentsDesigntype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
99
Quality 40%
88
Run on models
none yet
Process rating
C
55/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
Result and completion w 14
40
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: agentic-awesome-skills

How to improve

    For the model run — optional
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Broad scope meta-dynamic-shell SKILL.md:26
      Shell command executed automatically when the skill loads (Claude Code !`cmd` preamble)
      !`npx shadcn@latest info --json 2>/dev/null || echo '{"error": "No shadcn project found. Run shadcn init first."}'`

    Files scanned: 10. 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 55/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
    • 60Steps. 78 steps, 5 vague phrases
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4053 tokens
    • 100Consistency. Name and required fields are in place
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 13 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (6 tags): a typed call is more reliable
    • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 131: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 78 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.