Parcel Tracking

Erkennt automatisch den Paketdienst (DHL, Hermes, UPS, GLS, Amazon etc.) via Track123-API und ruft Tracking-Informationen ab. Optional PLZ für erweiterte Infos.

What to check before installing or running this skill: - The skill requires a TRACK123_API_SECRET (SKILL.md and track.py); supply only a Track123 API secret and not unrelated credentials. The registry summary incorrectly stated 'none' — prefer the SKILL.md's requirement. Use a minimal / revocable API key if possible. - The runtime only calls Track123 (default base https://api.track123.com/...). TRACK123_API_BASE can be overridden; confirm the base URL if you are concerned about redirecting requests to other endpoints. - The bundle includes track.py and a full Python virtualenv (many vendor packages). This is unusual because there is no install step that uses that venv and the skill will run with system python3. If you will run code locally, inspect the included files (especially track.py) and the venv contents or prefer to run in a sandboxed environment. - The pre-scan found unicode control characters in SKILL.md. Open SKILL.md in a hex/editor to see any invisible characters; remove them if they are unexpected. - If you want stronger assurance: review track.py (it is short and readable), run it in an isolated container or sandbox, and provide an ephemeral / least-privilege Track123 key you can revoke after testing. Overall, the behavior and credentials requested are coherent with parcel tracking via Track123, but verify the above inconsistencies and inspect the packaged venv before executing.

Type: OpenClaw Skill Name: parcel-tracking Version: 1.0.2 The skill's purpose is to track parcels using the Track123 API. It correctly retrieves the `TRACK123_API_SECRET` from an environment variable and uses it in HTTP headers for API calls to `https://api.track123.com`. Input parameters are used as expected in the API request. The included vendored libraries (`pip`, `certifi`, `charset_normalizer`, `idna`) are standard dependencies for network operations in Python. There is no evidence of malicious intent, such as unauthorized data exfiltration, arbitrary command execution, or prompt injection attempts in `SKILL.md`.