SKILLEMALL.ai

CD seedance-reference

Seedance 2.0/2.5 node wiring (ByteDance2ReferenceNode, ByteDance2TextToVideoNode, ByteDance2FirstLastFrameNode). Activate in the Query Templates when a Seedance template is selected, and in the Assemble Workflow when patching one — it carries the model-version choice, the reference-slot binding order, and which widgets each task locks. Prompt wording lives in the `prompting` skill's seedance fragment, not here.

szprivate/agentY Agent Skills author: szprivate 1 file body ≈ 1 262 tokens Open the sourcegithub.com↗ analyzed 36 h ago

Seedance 2.0/2.5 node wiring (ByteDance2ReferenceNode, ByteDance2TextToVideoNode, ByteDance2FirstLastFrameNode). Activate in the Query Templates when a…

As a process D 36/100 · Unfinished process — References files that are not bundled: references/seedance.md, references/seedance-2.5-full.md

ReferenceAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
98
Quality 40%
71
Run on models
none yet
Process rating
D
36/100
Unfinished process
References files that are not bundled: references/seedance.md, references/seedance-2.5-full.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-high-entropy-token SKILL.md:3
    High-entropy token-like string (may be an id, hash or a credential)
    description: Seedance 2.0/2.5 node wiring (Byte…ode, Byte…ode, Byte…ode). Activate in the Query Templates when a Seedance template is selected, and 
  • low Secrets in code secret-high-entropy-token SKILL.md:26
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | `Byte…ode` | first frame, or first + last | **no `ratio` widget at all** — the first frame's aspect ratio wins |
    table

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

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/seedance.md
  • warning missing-ref reference to a missing file: references/seedance-2.5-full.md

Process rating: all ten parameters 36/100

Will not run. References files that are not bundled: references/seedance.md, references/seedance-2.5-full.md
  • 0Tools and files. 2 referenced file(s) missing: references/seedance.md, references/seedance-2.5-full.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
  • 30Running it twice. 2 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 100Steps. 19 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1262 tokens

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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 414: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 19 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.