deepfake-detection
deepfake-detection is a Web research & fact-checking skill for AI agents, published by dirnbauer in the webconsulting-skills repository on GitHub. Skillspace rates deepfake-detection C (73/100) and it passed the safety scan; the rating is based on static analysis only.
Guides multimodal media authentication and deepfake forensics using provenance checks, metadata review, PRNU/noise analysis, temporal consistency, semantic forensics, and evidence reporting. Use when the user asks to verify images, audio, or video, investigate synthetic media, assess fake or manipulated content, or prepare a media authenticity report.
- Grade
- C
- Quality
- 73 / 100
- Safety
- Passed
- GitHub stars
- 32
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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