pinecone-memory

What to check before installing and running this skill: - Metadata mismatch: the registry metadata claims no required env vars, but the SKILL.md and code require PINECONE_API_KEY and Node.js. Assume PINECONE_API_KEY is required until the registry entry is corrected. - Install safely: run npm install in an isolated environment if you need to install dependencies. Review package.json (it depends on @pinecone-database/pinecone) and prefer installing in a controlled environment (container, VM) first. - Test with non-production credentials: use a throwaway Pinecone API key and a non-production index/namespace when you first run check/sync/heartbeat/cleanup. - Inspect default paths: by default the tool reads MEMORY.md and recursively reads the 'memory' folder — ensure these paths don't include sensitive files. If you pass custom paths, validate them carefully. - Be careful with destructive commands: cleanup deletes namespace data; restore/write operations modify your index. Don’t run cleanup/restore against production namespaces without backups and explicit confirmation. - Local artifacts: the tool writes .pinecone-memory-state.json and JSONL backups. Ensure these files are stored securely (they may contain excerpts of your memories) and exclude them from public repos. - Review code if you need higher assurance: the included tools/pinecone-memory.mjs is readable; if you are not comfortable, have a developer audit network calls and confirm there are no hidden endpoints beyond the Pinecone SDK usage. If you want, I can: - Summarize the remainder of tools/pinecone-memory.mjs (file was truncated in the manifest) and look specifically for network calls or surprising behavior, or - Produce a short checklist/command sequence to safely try this skill in a sandboxed environment.