AB alibabacloud-maxframe-video-frame-pipeline
This skill should be used when the user asks to "build a frame extraction job" / "视频抽帧 / 抽关键帧", "label driving images with a VLM" / "图像打标 / image labeling with Qwen-VL", "compute image embeddings" / "图像向量化 / multi-modal embedding", "build a video_table / image_table / clip_dir_table for AI FUNC", "扫 OSS 建 video meta 表", or mentions driving-scene / ADAS / 智驾 / 智能驾驶 / 自动驾驶 / 路测 / 行车记录仪 / 座舱 video or image pipelines on MaxFrame + OSS + ODPS. Not for audio (use driving-audio-maxframe-job).
This skill should be used when the user asks to "build a frame extraction job" / "视频抽帧 / 抽关键帧", "label driving images with a VLM" / "图像打标 / image labeling…
As a process B 72/100 · Nearly there — weak spots: running it twice, progress reporting
How to improve
- 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: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 72/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python, node) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 4264 tokens
- 100Steps. 60 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (11 tags): a typed call is more reliable
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
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +4Description says when NOT to use the skill
- +3Description length 490: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 60 items
- +3Output format is stated explicitly
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 100.