Recursive maths animator

Recursive maths animator — Manim-based technical animations with optional voiceover (manim-voiceover), git scene versioning, pinned requirements, asset folde...

This skill appears to do what it claims: Manim animation patterns, optional voiceover support, and a verification loop. However, before installing or running it: - Review any adapter that calls external TTS or GenAI services (references/gemini_tts_service.py and the use of manim-voiceover/gTTS). These modules perform network calls to third-party TTS/GenAI and will transmit your audio/text to external services. - The recommended 'vision verification loop' explicitly sends extracted frames for review in the host model/environment (Cursor/Claude Code). Treat rendered frames and any included images/fonts as potentially sensitive data and do not upload them to hosted models unless you accept that transmission. - Only set GEMINI_API_KEY or other credentials if you trust the adapter code. Inspect references/gemini_tts_service.py to confirm the endpoints and how the key is used. - Run the skill inside an isolated virtualenv or sandbox, and inspect scripts/run_pipeline.py and scripts/extract_verification_frames.py before execution to confirm they run only the commands you expect (no unexpected shell execs or uploads). - If you need to keep data local, avoid the verification loop that uploads frames, or perform verification locally (manual review) instead. If you want a more precise assessment, provide the full contents of references/gemini_tts_service.py and scripts/run_pipeline.py so I can check for exact network endpoints, credential usage, or any obfuscated/executable behavior.

Type: OpenClaw Skill Name: recursive-maths-animator Version: 1.7.0 The recursive-maths-animator skill bundle is a comprehensive and well-documented toolset for generating Manim-based animations with integrated voiceovers. It includes sophisticated features such as a Git-based project versioning system (manim_versioning.py), a library of pre-built animation patterns (pattern_library/), and a multimodal verification loop for AI agents to review rendered frames. While the code makes extensive use of the 'subprocess' module to interact with system tools like 'ffmpeg', 'manim', and 'git', and uses 'curl' to download fonts from Google (font_catalog.py), all such actions are transparently documented and strictly necessary for the skill's stated functionality. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found.