AC camscanner-image-detect-aigc
Use CamScanner to detect whether an image was generated by an AI model (e.g. Stable Diffusion, Midjourney, DALL·E). Powered by an AIGC-detection engine that classifies an image as genuine, suspected AI-generated, or AI-generated, with a confidence score. Returns a JSON result containing `ai_check_result` (1/2/3), `confidence`, and `result_text`. Use when the user asks whether a photo is AI-generated, wants to verify an image's authenticity against AI generation, or asks "is this AI art / Stable Diffusion / Midjourney?". Triggers on "检测AI生成", "是不是AI画的", "AIGC检测", "AI图片识别", "detect AI-generated image", "is this AI art", "is this diffusion / midjourney", or when the user shares an image and asks whether it was produced by AI.
Use CamScanner to detect whether an image was generated by an AI model (e.g. Stable Diffusion, Midjourney, DALL·E). Powered by an AIGC-detection engine that…
As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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: 2. 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 64/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 70When it triggers. States when to use, but not when not to
- 85Steps. 9 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1797 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +3Description length 732: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 9 items
- +4Has examples (6 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.