BB zhongcao-cover-maker
Turn a photo, a topic idea, or an accepted draft into a scroll-stopping REDnote (Xiaohongshu) cover and post image. This AI cover generator creates vertical 3:4 Xiaohongshu note covers with clean backgrounds, bold focal composition, and text-safe areas for beauty, food, fashion, travel, and knowledge content. Generate high-click Xiaohongshu note covers, OOTD post images, food photography covers, product recommendation visuals, and lifestyle note illustrations from one photo or a topic description. Start from a real photo, compose from multiple references, or refine an accepted cover toward a publish-ready result. Optionally it reads Xiaohongshu itself — the notes already running for the topic, one page of a note's top comments, and an account's own recent notes — so Xiaohongshu research, competitor note analysis and comment analysis rest on the platform instead of on guesswork.
Turn a photo, a topic idea, or an accepted draft into a scroll-stopping REDnote (Xiaohongshu) cover and post image.
As a process B 70/100 · Nearly there — weak spots: result and completion, inputs and preconditions, progress reporting
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.
Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 1
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high Concealment
en-hide-from-userreferences/note-lookup.md:29Instruction to hide actions from the userDo not tell the user Xiaohongshu costs ten times Douyin without saying which read you mean.
Files scanned: 18. 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 70/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Inputs and preconditions. Does not say what the process needs to start
- 50When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Steps. 22 steps
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2680 tokens
- 100Running it twice. Mutating operations check current state
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 890: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -32 of 3 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 9 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (12 of 12)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.