AF viral-video-studio
Full short-form video content creation workflow for TikTok, Instagram Reels, and YouTube Shorts: analyze a reference viral video URL, reverse-engineer its viral structure using the 7 psychological triggers framework, generate AI image prompts for each scene, create a detailed shooting script with text overlays, build a posting schedule, and produce a monetization roadmap. Use when: (1) user provides a TikTok/Reels/Shorts link and wants to create similar content, (2) user wants to build a viral short video channel from scratch, (3) user needs a content calendar for channel growth, (4) user wants AI-generated image prompts for short videos, (5) user asks about making viral videos, content strategy, or growing a TikTok channel.
As a process F 33/100 · Will not run — References files that are not bundled: assets/character-sheet.md
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: assets/character-sheet.md
Process rating: all ten parameters 33/100
- 0Tools and files. 1 referenced file(s) missing: assets/character-sheet.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 7 mutating operations with no state check
- 100Steps. 54 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3008 tokens
- low 11 top-level sections: this looks like several domains in one skill
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
- -31 of 1 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 734: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 54 items
- +4Has examples (11 code blocks)
- +4Reference files are cited in the instructions (9 of 9)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.