Meal Planner Pro

Every household faces the same exhausting question every single day: 'What's for dinner?' Meal Planner Pro learns your family's unique tastes, allergies, and...

This skill appears coherent and low-risk in that it is instruction-only and stores data locally under data/ and config/. Before installing: 1) Confirm your OpenClaw runtime enforces the skill's file-path restrictions (only data/ and config/) and does not grant broader filesystem access. 2) The skill uses vision-capable LLMs for fridge photos — images and their parsed text will be sent to whatever model provider your agent uses; if you rely on a third-party LLM, consider privacy implications. 3) The dashboard spec references optional external services (Supabase, Next.js) — you only need to provide credentials if you choose to build and host the dashboard; do not supply unrelated API keys. 4) The setup writes files and tightens permissions (umask/chmod) — review the commands if you have specific security policies. 5) The SKILL.md includes explicit prompt-injection defenses (the scanner flagged patterns), which is intentional; still audit runtime handling of untrusted recipe text to ensure the agent doesn't treat user-pasted or scraped recipe content as executable instructions. If you need stronger assurances, run the skill in a sandboxed environment and review the created data files after first run.

Type: OpenClaw Skill Name: normieclaw-meal-planner-pro Version: 1.0.3 The Meal Planner Pro skill bundle is a well-structured and security-conscious AI agent for household meal management. It includes explicit prompt-injection defenses in SKILL.md, instructing the agent to treat external recipe data as untrusted string literals and enforcing strict regex-based allowlists for file path access. The setup process in SETUP-PROMPT.md uses defensive shell commands with restrictive file permissions (umask 077, chmod 600) to protect sensitive dietary data. The comprehensive dashboard specification and database schema further emphasize security best practices, such as Row-Level Security (RLS) and private storage buckets for user-uploaded images. No indicators of malicious intent, data exfiltration, or unauthorized execution were found.