帮你写大众点评的Skill
v1.0.0写大众点评风格的本地生活评论。当用户发餐厅/菜品照片说"写点评"、"帮我评价"、"写个大众点评"、"生成点评文案"时使用。
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by申悦@s2dongman
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match the SKILL.md: the skill is an instruction-only writer for Dianping-style reviews. All declared requirements are empty (no env vars, no binaries), which is proportionate for a text-generation/photo-captioning helper. The need to 'recognize dishes from photos' is consistent with a vision-enabled LLM workflow.
Instruction Scope
SKILL.md stays on-topic: it describes how to pick review elements, phrasing rules, how to request missing user inputs (location, environment, service, negatives), and to generate multiple variants. It does not instruct the agent to read unrelated files, access system config, or transmit data to unexpected endpoints. The only external action implied is using the model to identify dishes from images, which is appropriate for the stated feature.
Install Mechanism
No install spec and no code files are present. This lowers risk because nothing will be written to disk or fetched during install. Instruction-only skills are expected for prompt/templates like this.
Credentials
The skill requires no environment variables, credentials, or config paths. That is proportionate for a review-generation skill. There are no unexpected secret accesses in the instructions.
Persistence & Privilege
always is false and the skill is user-invocable, which is standard. It does not request persistent system privileges or modify other skills' configs. Autonomous invocation is allowed by default but not elevated here.
Assessment
This skill is instruction-only and internally consistent with its purpose: it will use the model (including vision if available) to identify dishes from user photos, ask the user any missing context (location, environment, service, flaws), and produce 3 colloquial Dianping-style review variants. It requests no credentials and installs nothing. Consider privacy: images and any location/address you provide will be processed by the agent and (depending on your platform) routed to the model provider — avoid sending sensitive or identifying information if you don't want it shared. If you need greater assurance, ask the skill author how image data is handled by the platform or request an explicit statement about whether any data leaves your environment.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.