AC tandian-image-skills
本地生活探店图像处理 skill。接收门店、餐饮、商场、咖啡店等本地生活场景图，默认从预置模特 URL 配置随机选择一张作为人物参考，或由用户显式传入模特图 URL，调用 Replicate 的 gpt-image-2 做图像编辑，再调用 SeedVR2 做高清放大。用户提到探店图、门店场景合成、模特放入店铺场景、美女角色迁移、Replicate 图像编辑、SeedVR2 放大时使用。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 32 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 721 tokens
- 100Running it twice. No mutating operations
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
- +1No license
- +2Single-language instructions
- +3Description length 194: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (7 code blocks)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: clean
This skill transparently uses Replicate-based image editing and upscaling on user-selected images, with privacy-relevant uploads but no hidden or unrelated behavior found.
LLM: benign (high) · VirusTotal: benign · 28 May 2026