SKILLEMALL.ai

CD seedance-motion-design-ad

Generate motion design advertisement video prompts for software and tech companies using Seedance 2.0 on Higgsfield. Use whenever the user wants to create a software product ad, SaaS promo, app launch video, tech demo, UI showcase, startup video, or motion graphics for a tech company. Triggers on: software ad, SaaS video, product launch, app promo, tech commercial, UI animation, motion design ad, startup video, product demo video, feature showcase, or any software/tech promotional video request. Use even for "make a video for my app" or "promo for our platform.

beshuaxian/higgsfield-seedance2-jineng Agent Skills author: beshuaxian 1 file body ≈ 14 185 tokens Open the sourcegithub.com↗ analyzed 15 h ago

Generate motion design advertisement video prompts for software and tech companies using Seedance 2.0 on Higgsfield. Use whenever the user wants to create a…

As a process D 43/100 · Unfinished process — weak spots: inputs and preconditions, failures and branches, consistency

GeneratorMedia and videoMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
C
84/100
safety, quality, tests
Safety 60%
99
Quality 40%
62
Run on models
none yet
Process rating
D
43/100
Unfinished process
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • 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-security SKILL.md:392
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - Lateral movement + opacity

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.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 motion design advertisement video prompts for software an… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning body-long SKILL.md body ≈ 14185 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 43/100

  • 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. 11 mutating operations with no state check
  • 40Consistency. Frontmatter name (seedance-motion-design-ad) differs from the folder (06-motion-design-ad)
  • 40Execution cost. Instruction body is 14185 tokens: crowds the task out of the window
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 60Steps. 439 steps, 9 vague phrases
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 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)
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 567: enough signal without eating the budget
  • +4Structure: 110 headings
  • +3Step-by-step instructions: 439 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.