Huckleberry

Track baby sleep, feeding, diapers, and growth via Huckleberry app API. Use for logging baby activities through natural language.

What to consider before installing: - The SKILL.md and code require HUCKLEBERRY_EMAIL/HUCKLEBERRY_PASSWORD or a credentials file (~/.config/huckleberry/credentials.json); the registry metadata does not list these — expect to supply secrets if you use it. - The script imports google.cloud.firestore and directly reads/writes Firestore documents (api._get_firestore_client()). That may cause the script to use Google Application Default Credentials (GOOGLE_APPLICATION_CREDENTIALS or gcloud user creds) if they exist — be careful: it can access other Google project credentials present on the host. - The package installation is a pip install from a GitHub repo (not a vetted PyPI release). Review the upstream py-huckleberry-api repo and the included scripts/hb.py source yourself before installing. - If you decide to use it: run in an isolated environment (dedicated VM/container or virtualenv), create a Huckleberry account with least-privilege credentials, avoid reusing sensitive Google credentials, and inspect the code paths that call Firestore to ensure writes are intended. - If you need a cleaner trust boundary, request the publisher add explicit metadata for required env vars/config paths and document the Firestore usage (why direct Firestore access is necessary) so you can assess risk more precisely.

Type: OpenClaw Skill Name: openclaw-huckleberry-skill Version: 0.1.0 This skill is classified as suspicious due to its reliance on a reverse-engineered API client (`py-huckleberry-api` from GitHub) and its direct interaction with Google Cloud Firestore. While the current implementation uses Firestore for benign purposes (extending note functionality and precise sleep logging), this direct, low-level access to the backend data store (as seen in `scripts/hb.py` via `api._get_firestore_client()` and `add_notes_to_latest_interval()`) represents a powerful capability that, if misused, could lead to unauthorized data manipulation or exfiltration. The installation from a GitHub URL also introduces a supply chain risk. There is no clear evidence of intentional malicious behavior, but these risky capabilities warrant a 'suspicious' classification.