AB YouTube Launch Kit
Turn a video topic, rough notes, or transcript into a complete YouTube launch package. Outputs two title variants, a keyword-optimized description with timestamped chapters, 10 tags, a pinned comment, a discussion seed (also known as first comment prompt or first pinned comment), an optional thumbnail prompt, and an optional 3-tweet promo set. Use when a creator pastes a video topic, outline, notes, or transcript and asks for a title, description, tags, launch copy, pinned comment, first comment prompt, discussion seed, thumbnail idea, or promo tweets for YouTube.
As a process B 73/100 · Nearly there — weak spots: result and completion, consistency, running it twice
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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - note
frontmatter-keyunknown frontmatter key "slug"
Process rating: all ten parameters 73/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (YouTube Launch Kit) differs from the folder (youtube-launch-kit)
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 47 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 6 branches, has a failure section
- 100Execution cost. Instruction body is 2404 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 570: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 47 items
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.