SKILLEMALL.ai

BB ui-demo

Record polished UI demo videos using Playwright. Use when the user asks to create a demo, walkthrough, screen recording, or tutorial video of a web application. Produces WebM videos with visible cursor, natural pacing, and professional feel.

The skillemall take

Promises to record polished demo videos of web apps via Playwright with visible cursor and natural pacing. One instruction file at 3739 tokens, no scripts. Grade B: quality 85%, process 68%, no critical findings.

In practice, should generate WebM with proper visuals, but the process score lagging behind quality suggests friction points—likely in reproducibility or pacing details. Safety maxed out, compatible across all major platforms. Worth installing if you need automated screencasts: it works, but verify the first output.

affaan-m/everything-claude-code Agent Skills author: affaan-m MIT 1 file body ≈ 3 739 tokens Open the sourcegithub.com↗ analyzed 23 h ago

Record polished UI demo videos using Playwright.

As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, running it twice

ProcedurePlaywrightMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
68/100
Nearly there
Inputs and preconditions w 11
0
Failures and branches w 10
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

The same skill appears in 2 more places: RA-Skills, RA-Skills

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: 1. 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 68/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 6 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 54 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3739 tokens
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (3 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)
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 241: enough signal without eating the budget
    • +4Structure: 26 headings
    • +3Step-by-step instructions: 54 items
    • +3Output format is stated explicitly
    • +4Has examples (13 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.