SKILLEMALL.ai
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BD oil-motion

处理视频和序列帧，编译滚动、指针、拖动与状态驱动的网页动效；内含本地媒体处理脚本和运行时。新素材生成使用宿主工具。

The skillemall take

Promises to compile web animations from video and frame sequences: scroll, pointer, drag, state changes. Includes local media processing scripts and runtime. New materials generated via host tools.

The package contains 32 files and 14 scripts with no critical errors. Code quality scores 74 out of 100, execution flow 43. Sandbox not tested, model runs skipped. Requires external tools; specifics not clarified in description. Install if you're comfortable with undocumented dependencies and willing to dig into setup details.

nexu-io/open-design Agent Skills author: nexu-io Apache-2.0 32 files · 14 scripts body ≈ 1 726 tokens Open the sourcegithub.com↗ analyzed 5 d ago

处理视频和序列帧，编译滚动、指针、拖动与状态驱动的网页动效；内含本地媒体处理脚本和运行时。新素材生成使用宿主工具。

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentAI and agentsMedia and videotype 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
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
D
43/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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.
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: 32. 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")
  • note frontmatter-key unknown frontmatter key "en_name"
  • note frontmatter-key unknown frontmatter key "zh_name"
  • note frontmatter-key unknown frontmatter key "zh_description"
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "od"

Process rating: all ten parameters 43/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 49 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1726 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)
  • +3Description length 57: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 49 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (12 of 12)
  • +3All 11 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

In the sandbox The scripts kept to themselves

The skill's scripts were run in a throwaway machine: no network, fake keys in the home directory, a tracer watching. We wrote down what they did. Reaching for the network or for secrets caps the technical grade at C; a quiet run adds no points.

Запущено 12 скриптов, ещё 2 не поместились в лимит; каждому дали двадцать секунд, поддельный домашний каталог с ключами и сеть, в которой ничего нет.

Из них 8 не дошли до работы, и об их поведении мы ничего не узнали.

assets/chroma-video-renderer.tsничего за пределами своей папки
assets/interactive-motion.tsничего за пределами своей папки
assets/step-gesture.tsничего за пределами своей папки
scripts/chroma_key.pyне запустился: ModuleNotFoundError: No module named 'numpy'
scripts/compile_scroll_video.pyне запустился: ModuleNotFoundError: No module named 'PIL'
scripts/compose_travel_frames.pyне запустился: ModuleNotFoundError: No module named 'PIL'
scripts/composite_alpha_keyframe.pyне запустился: ModuleNotFoundError: No module named 'PIL'
scripts/create_explainer.pyне запустился: create_explainer.py: error: the following arguments are required: --atlas-url, --output
scripts/loop_cleanup.pyне запустился: ModuleNotFoundError: No module named 'PIL'
scripts/media_edges.pyничего за пределами своей папки
scripts/motion_budget.pyне запустился: motion_budget.py: error: the following arguments are required: --frames, --display, --time-control, --background-owner
scripts/motion_pipeline.pyне запустился: ModuleNotFoundError: No module named 'PIL'

16 Oct 2026