AC image-ppt-maker
Create PPT-style images through a human-in-the-loop workflow: clarify presentation requirements including optional top-corner LOGO space, research and draft McKinsey-style master and page-by-page outlines, expand page content, confirm the desired visual style before image prompts, write unified-style image-2 prompts, batch-generate 16:9 slide images, automatically assemble the images into a playable 16:9 HTML slideshow, and finally write oral speaker notes based on the outline and final images. Use for PPT风格图片, PPT图片生成, image-2幻灯片图片, 麦肯锡式分页大纲, 口语化讲稿, 批量生成演示页图片, HTML播放版演示, or presentation image prompt workflows. This skill does not assemble PPTX files.
Create PPT-style images through a human-in-the-loop workflow: clarify presentation requirements including optional top-corner LOGO space, research and draft…
As a process C 60/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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: 7. 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 60/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 85Steps. 51 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1757 tokens
- 100Progress reporting. Reports progress
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 659: enough signal without eating the budget
- +4Structure: 5 headings
- +3Step-by-step instructions: 51 items
- +4Reference files are cited in the instructions (3 of 3)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.