CC seedance-cinematic
Generate cinematic film-style video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants cinematic, film-like, movie-quality, Hollywood-style, dramatic, or professional film-quality AI video. Triggers on: cinematic, film look, movie scene, dramatic lighting, depth of field, lens flare, anamorphic, letterbox, noir, epic, Steadicam, dolly, crane shot, or any cinematic video generation request. Always use this skill even if the user doesn't explicitly say "cinematic" but describes a film-like aesthetic.
Generate cinematic film-style video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants cinematic, film-like, movie-quality, Hollywood-style…
As a process C 59/100 · Has gaps — weak spots: inputs and preconditions, consistency, execution cost
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
-
low Risky intent
intent-offensive-securitySKILL.md:461Offensive-security / dual-use content (legitimate for authorised testing; review intended use)| **Truck Left / Truck Right** | Lateral movement without subject reframing, shows environment | 2–4 sec | "Camera trucks left 10 feet at 2 feet/second. Subject remains frame-right. Reveals background
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 cinematic film-style video prompts for Seedance 2.0 on Hi… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
body-longSKILL.md body ≈ 22337 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 59/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 10Execution cost. Instruction body is 22337 tokens: crowds the task out of the window
- 30Running it twice. 92 mutating operations with no state check
- 40Consistency. Frontmatter name (seedance-cinematic) differs from the folder (01-cinematic)
- 60Result and completion. Output format stated, no completion criterion
- 60Failures and branches. 2 branches
- 70When it triggers. States when to use, but not when not to
- 85Steps. 299 steps, 3 vague phrases
- 100Tools and files. No external tools needed
- low 15 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 520: enough signal without eating the budget
- +4Structure: 56 headings
- +3Step-by-step instructions: 299 items
- +3Output format is stated explicitly
- +4Has examples (18 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.