AC viral-restaurant-marketing
Use this skill when a restaurant owner or marketer needs help with: viral TikTok/Instagram content strategy, content calendar generation, hook writing, Google Reviews growth, or website conversion optimization. Built on real results: millions of views achieved for restaurant clients. Triggers on keywords like "restaurant marketing", "TikTok restaurant", "viral food content", "restaurant social media", "meer klanten restaurant", "restaurant Instagram", "restaurant TikTok", "Google Reviews restaurant".
As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 506 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "scripts" - note
frontmatter-keyunknown frontmatter key "references"
Process rating: all ten parameters 55/100
- 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
- 30Running it twice. 3 mutating operations with no state check
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 131 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3464 tokens
- low 12 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -42 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +3Description length 505: enough signal without eating the budget
- +4Structure: 28 headings
- +3Step-by-step instructions: 131 items
- +4Has examples (5 code blocks)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.