SKILLEMALL.ai
GitHub ↗ RU Sign in

CD seedance-fashion-lookbook

为 Seedance 2.0（Higgsfield）生成时尚造型书、模特展示和风格视频提示。在用户想要时尚视频内容、造型书视频、模特走秀、服装展示、风格指南、时尚活动、跑道片段、街头风格内容或任何时尚/服装视频时使用。在以下情况下触发：时尚视频、造型书、模特展示、服装、风格指南、时尚活动、跑道、街头风格、系列发布、时尚广告、服装视频、OOTD、时尚电影或任何时尚/模特视频请求。即使是"展示这件服装"或"为我的品牌提供时尚内容"也适用。

beshuaxian/higgsfield-seedance2-jineng Agent Skills author: beshuaxian 1 file body ≈ 21 171 tokens Open the sourcegithub.com↗ analyzed 15 h ago

为 Seedance…

As a process D 48/100 · Unfinished process — weak spots: when it triggers, inputs and preconditions, consistency

ProcedureMedia and videoMarketingtype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
D
48/100
Unfinished process
Inputs and preconditions w 11
0
Progress reporting w 2
0
Execution cost w 6
10
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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 · 0

✓ No critical or high findings

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

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 21171 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 48/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 10Execution cost. Instruction body is 21171 tokens: crowds the task out of the window
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 34 mutating operations with no state check
  • 40Consistency. Frontmatter name (seedance-fashion-lookbook) differs from the folder (zh-CN)
  • 55Failures and branches. 1 branches
  • 60Steps. 134 steps, 7 vague phrases
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. No external tools needed
  • low 18 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)
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 219: enough signal without eating the budget
  • +4Structure: 138 headings
  • +3Step-by-step instructions: 134 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)

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