Download videos from public LinkedIn posts as MP4 files without authentication or dependencies, saving them at the best available quality.

What to check and consider before installing/running: - The skill includes source (main.go) but the registry metadata does not declare that you need the Go toolchain; you will need 'go' installed to build or use the code. Treat the build step as required. - Source provenance is unknown (owner ID and homepage missing). If you don't trust the source, review the Go source yourself or build the binary in an isolated environment (sandbox/VM) before running it on your main system. - The program fetches LinkedIn post pages and downloads content from LinkedIn's CDN (dms.licdn.com). This is expected for the stated purpose but may violate LinkedIn's terms of service in some jurisdictions or for some content — consider legality and copyright before downloading. - The tool writes files into the current directory and renames a .tmp file on success; ensure you run it in a directory where writing files is acceptable. - Network connectivity is required; if you need to audit network calls, run the program in a network-monitored environment (or patch the code to log URLs before downloading). - If you want to reduce risk: (1) manually inspect main.go (you already have it), (2) build the binary from source on an isolated machine, (3) run it with a non-privileged user, and (4) avoid running it against private or authenticated content. If you want a cleaner approval (verdict: benign), supply verifiable upstream source (a maintained repo or release) or update the registry metadata to declare the 'go' build requirement and a homepage/owner contact so provenance can be validated.

Type: OpenClaw Skill Name: linkedin-video-dl Version: 1.0.0 The OpenClaw skill bundle `linkedin-video-dl` is classified as benign. The `SKILL.md` and `README.md` files provide clear, non-malicious instructions for building and using a Go CLI tool to download videos from public LinkedIn posts, with no evidence of prompt injection. The `main.go` source code implements this functionality by fetching HTML from `linkedin.com`, extracting video URLs specifically from LinkedIn's CDN (`dms.licdn.com`), and downloading the video to a local file. The code uses only standard Go libraries, sanitizes filenames to prevent path traversal, and does not exhibit any signs of data exfiltration, malicious execution, persistence, or obfuscation.