Skillv0.1.0

ClawScan security

PPT Audio To Video · ClawHub's context-aware review of the artifact, metadata, and declared behavior.

Scanner verdict

BenignMar 12, 2026, 7:07 AM

Verdict: benign
Confidence: high
Model: gpt-5-mini
Summary: The skill's code and runtime instructions are coherent with its stated purpose (turning narration + slides into a narrated MP4); it requires standard local tooling (ffmpeg, pdftoppm, whisper-cpp) and works on local files, with no signs of credential access or hidden network exfiltration.
Guidance: This skill appears to do what it says and operates on local files. Before installing or running it: 1) ensure your environment has the required tools (ffmpeg, ffprobe, pdftoppm/poppler, whisper-cpp) since metadata does not declare them; 2) expect to download a Whisper model binary from Hugging Face (check license, size, and trust the URL before downloading); 3) scripts operate on files you provide and will write outputs (CSV, ffconcat, MP4) to working directories — review/output paths before running; 4) if you need to run on sensitive audio, note that transcription happens locally if you use whisper-cpp, but if you substitute a cloud ASR you should review that service's privacy; and 5) review the two bundled Python scripts (they are short and readable) if you want full assurance — they do not perform network calls or access unrelated credentials.

Review Dimensions

Purpose & Capability: noteThe skill's name/description match the included scripts and SKILL.md: extracting text from PPTX, producing slide images, transcribing audio, building a timing CSV, and rendering via ffmpeg is expected. One minor inconsistency: the registry metadata lists no required binaries/env vars, but the SKILL.md explicitly requires ffmpeg/ffprobe/pdftoppm and whisper-cpp (and a whisper model). This is reasonable for the task but the metadata omission means the platform won't automatically surface those runtime dependencies.
Instruction Scope: okSKILL.md stays on task: it references only slide files, audio files, timing CSVs, local model downloads, and standard tools. The instructions do suggest downloading a model from Hugging Face and using platform-specific exporters (Keynote/PowerPoint/soffice) which are expected for slide rendering; there are no instructions to read unrelated system files or to transmit data to unexpected endpoints beyond the model download URL.
Install Mechanism: okThis is instruction-only with two small helper scripts; there is no install spec. The SKILL.md suggests installing via brew and downloading a model with curl from Hugging Face — those are normal but are network operations performed at runtime by the user/agent, not packaged installers. No arbitrary or obfuscated remote code downloads are embedded in the skill files.
Credentials: okThe skill requests no environment variables or credentials. The files and tools it uses (local PPTX/PDF/images/audio, whisper model binary, ffmpeg) are proportional to the stated functionality. There are no requests for API keys, cloud credentials, or unrelated secrets.
Persistence & Privilege: okalways is false and the skill does not request special persistent privileges or modify other skills/system configs. It runs local scripts and spawns ffmpeg as expected; autonomous invocation is allowed by platform default but is not combined with other red flags here.