Social Media Scheduler
v1.0.0Generate a full week of social media content for any topic. Outputs platform-optimized posts for Twitter/X, LinkedIn, and Instagram with hashtags and posting...
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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 provided files: a small Bash script plus documentation that generate a week of platform-optimized draft posts. Required tools (bash, cat, common POSIX utilities) are proportionate to the task.
Instruction Scope
SKILL.md and generate.sh are limited to producing content-calendar.md in the current directory from the supplied topic/audience. One minor operational note: the script unconditionally writes/overwrites content-calendar.md (cat > "$OUTPUT"), so running it in a directory with an existing file will replace that file without prompting.
Install Mechanism
No install spec or external downloads; this is an instruction-only skill with an included shell script. Nothing is fetched from the network or written outside the current working directory.
Credentials
The skill requests no environment variables, no credentials, and does not read config paths. The script only reads its positional args and standard date/locale utilities.
Persistence & Privilege
The skill does not request permanent presence (always:false) and does not attempt to modify other skills or system-wide settings. It runs locally when invoked.
Assessment
This skill is coherent and low-risk: it generates a local markdown file from the topic and optional audience and does not access the network or require secrets. Before running, inspect generate.sh (you already have it) and: 1) back up any existing content-calendar.md because the script will overwrite it; 2) run it in a dedicated directory if you want to avoid accidental file replacement; 3) note that topic normalization removes non-alphanumeric characters and lowercases tags (e.g., "Sustainable Fashion" -> #sustainablefashion), so check hashtags for readability; 4) if you plan to use an LLM as the SKILL.md suggests, be aware that piping to an external model may send your topic/audience text to that model—review that model's privacy policy before sending sensitive content.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.