Local STT with selectable backends - Parakeet (best accuracy) or Whisper (fastest, multilingual).
Security Analysis
high confidenceThe skill largely does what it says (local STT) but it reads ~/.env files and uses Matrix credentials without declaring them, and will download models at runtime — behavior the registry metadata doesn't disclose and that could expose secrets or send transcripts externally if used.
The code and SKILL.md align with a local STT tool (ffmpeg conversion, ONNX-based Parakeet/Whisper backends). The ability to post transcriptions to a Matrix room matches the documented --room-id option. However, the registry metadata listed no required environment variables while the script clearly expects MATRIX_HOMESERVER and MATRIX_ACCESS_TOKEN when the Matrix feature is used; that mismatch is noteworthy.
SKILL.md documents the --room-id option but does not mention that the runtime will: (1) attempt to load environment files from ~/.openclaw/.env and ~/.env, (2) read MATRIX_HOMESERVER and MATRIX_ACCESS_TOKEN from the environment, (3) write logs to /tmp/stt_matrix.log, and (4) load models via onnx_asr which typically pulls model files from network sources (e.g., huggingface). Reading a user's ~/.env is scope-creep because it can surface unrelated secrets; automatic model downloads are network activity not called out in metadata.
There is no install spec (instruction-only), which minimizes installer risk. The script includes a commented dependency list and a nonstandard shebang ('uv run --script') indicating runtime packages will be required; this implies runtime package installation/network activity but no explicit installer URL or archive is used.
The skill requests no environment variables in registry metadata, yet the script loads ~/.openclaw/.env and ~/.env and reads MATRIX_HOMESERVER and MATRIX_ACCESS_TOKEN if present. Automatically loading a user's .env and using tokens is disproportionate unless clearly documented; it increases the chance of accidental use of unrelated secrets. The Matrix access token, if present, will be used to transmit transcriptions to the specified homeserver.
The skill is not always-enabled and does not request elevated platform privileges. It writes a local log file (/tmp/stt_matrix.log) and temporarily writes a converted WAV file before deleting it, which is reasonable for this CLI. It does not modify other skills or agent-wide configuration.
Guidance
This skill appears to be a legitimate local STT tool, but you should be cautious before installing or using it as-is: - The script will automatically load ~/.openclaw/.env and ~/.env and may pick up sensitive environment variables. Review the contents of those files first or move secrets elsewhere. - If you use --room-id (Matrix integration), the script will look for MATRIX_HOMESERVER and MATRIX_ACCESS_TOKEN and will send the transcript to the specified homeserver; provide a minimally-privileged token or avoid the feature if you don't trust the destination. - The tool uses onnx_asr/huggingface components to load models at runtime; expect network downloads of model weights (possibly large) from external hosts. If you require offline-only operation, ensure required models are pre-provisioned and verify the code's model-loading behavior. - The script writes a local log (/tmp/stt_matrix.log) containing attempt metadata (URLs and HTTP status codes). Inspect this file for unexpected behavior. Recommended actions: ask the skill author to update registry metadata to declare required env vars (MATRIX_HOMESERVER, MATRIX_ACCESS_TOKEN) and to explicitly document network/model downloads; or run the skill in an isolated environment (container or VM) with only the minimal credentials you are willing to expose.
Latest Release
v1.0.0
- Initial release of unified local speech-to-text with ONNX Runtime and int8 quantization. - Supports selectable backends: Parakeet (default, best English accuracy) and Whisper (fastest, multilingual). - Easily switch backends and models via command-line options. - Includes benchmarking data for model speed and accuracy. - Requires ffmpeg for operation.
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