AC Podcast Episode Launch Pack
Turn a podcast transcript, episode outline, or topic into a complete launch package. Outputs episode titles (curiosity + clarity variants), full show notes with timestamps and key takeaways, a subscriber email blast, and an Instagram audiogram caption — plus optional pull quotes, a LinkedIn post draft, and a promo tweet thread. Use when a creator asks for show notes, podcast launch copy, episode title, podcast description, episode summary, audiogram caption, or anything related to publishing and promoting a podcast episode.
As a process C 63/100 · Has gaps — 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 63/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 5 mutating operations with no state check
- 40Consistency. Frontmatter name (Podcast Episode Launch Pack) differs from the folder (podcast-episode-launch-pack)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Failures and branches. 7 branches
- 100Steps. 44 steps
- 100When it triggers. States when to use and when not to
- 100Execution cost. Instruction body is 3172 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 529: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 44 items
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.