SKILLEMALL.ai
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Build distinct UI variants behind a development-only picker and integrate the variant the user selects.

The skillemall take

Promises to hide multiple UI variants behind a dev-only picker and apply the selected one. Three files, 2105 tokens, no scripts. No critical issues found, but quality stuck at 70, process at 57. No model runs or sandbox tests—whether it actually works is your guess. Supports Claude, Cursor, Gemini, DeepSeek and others. Worth installing if you need this pattern and can verify it yourself on your setup.

sickn33/agentic-awesome-skills Claude Code author: sickn33 3 files body ≈ 2 105 tokens Open the sourcegithub.com↗ analyzed 25 h ago

Build distinct UI variants behind a development-only picker and integrate the variant the user selects.

As a process C 57/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmentData and analyticsCommercetype 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
C
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "risk"
    • note frontmatter-key unknown frontmatter key "source"
    • note frontmatter-key unknown frontmatter key "source_repo"
    • note frontmatter-key unknown frontmatter key "source_type"
    • note frontmatter-key unknown frontmatter key "date_added"
    • note frontmatter-key unknown frontmatter key "license_source"

    Process rating: all ten parameters 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 5 mutating operations with no state check
    • 65Failures and branches. 3 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 11 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2105 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (6 tags): a typed call is more reliable

    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 103: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • -5TODO / placeholder text left in the skill
    • +2Single-language instructions
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 11 items
    • +1License stated

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