CD seedance-food-beverage
Generate food and beverage video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants food videos, recipe content, restaurant promos, beverage ads, cooking videos, food ASMR, menu showcases, food delivery ads, café content, or any food/drink video. Triggers on: food video, recipe, cooking, restaurant, beverage, food ad, food ASMR, menu, café, cocktail, food photography video, appetite appeal, food styling, mukbang, or any food/drink video request. Use even for "make my food look delicious" or "restaurant promo video.
Generate food and beverage video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants food videos, recipe content, restaurant promos, beverage…
As a process D 47/100 · Unfinished process — weak spots: inputs and preconditions, failures and branches, consistency
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.
Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Obfuscation
uni-mixed-script-wordSKILL.md:560Word mixing Latin and Cyrillic letters (homoglyph obfuscation) (1 occurrence)**Hero Moment**: The final 3 seconds of latte art being poured. The completed design (leaf, heart, or rosetта) coming into full view as the pour concludes.
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Generate food and beverage video prompts for Seedance 2.0 on Higgs… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
body-longSKILL.md body ≈ 12936 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 47/100
- 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
- 30Running it twice. 26 mutating operations with no state check
- 40Consistency. Frontmatter name (seedance-food-beverage) differs from the folder (14-food-beverage)
- 40Execution cost. Instruction body is 12936 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 85Steps. 503 steps, 3 vague phrases
- low 17 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)
- +1No license
- +2Single-language instructions
- +3Description length 537: enough signal without eating the budget
- +4Structure: 99 headings
- +3Step-by-step instructions: 503 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.