reverse-trace
Identify the source of an image or video frame — TV show episode, movie scene, geographic location, or original publication. This skill should be used when the user asks to identify where an image is from, trace a screenshot back to its source, geolocate a photo, find what show or movie a frame is from, or do a reverse image search. Chains Google Vision, Picarta geolocation, and Gemini in parallel with graceful degradation. Triggers on: reverse image search, identify source, what show is this, where was this taken, trace image, identify video, what movie, which episode, geolocate photo, image
npx skills add majiayu000/claude-skill-registry --skill reverse-trace --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Reverse Trace Identify the source of images and videos by running multiple reverse search APIs in parallel and synthesizing results into a confidence-ranked report. Each engine contributes a different signal — web entity matching, AI geolocation, multimodal LLM identification — and the orchestrator merges them because no single API reliably covers all identification scenarios. ## Prerequisites At least one API credential must be set. Missing keys cause the orchestrator to skip that engine, not crash. | Engine | Env Var | Free Tier | Signal | |--------|---------|-----------|--------| | Google Vision | `GOOGLE_APPLICATION_CREDENTIALS` or ADC | 1K/mo | Web entities, matching pages, similar images, best-guess labels | | Picarta (geospy) | `PICARTA_API_KEY` or `GEOSPY_API_KEY` | Yes | Lat/lng, city, country, confidence score | | Gemini | `GOOGLE_API_KEY` or `GEMINI_API_KEY` | Yes | Media type, title, season/episode, characters, actors | To set up Vision ADC: `gcloud auth application-default login` ## Workflow ### Full pipeline (recommended default) Run `rt_trace.py` to execute all available engines in parallel. For video input, keyframes are extracted first via ffmpeg. ```bash python3
- Prerequisites
- Workflow
- Full pipeline (recommended default)
- Individual engines
- Engine selection guide
- Output format
- Adding new engines
python3 scripts/rt_trace.py image.jpg python3 scripts/rt_trace.py video.mp4 --max-frames 3 python3 scripts/rt_trace.py image.jpg --json python3 scripts/rt_trace.py image.jpg --skip geospy python3 scripts/rt_trace.py image.jpg --engines vision gemini python3 scripts/rt_vision.py image.jpg # Web entities + matching pages python3 scripts/rt_geospy.py photo.jpg --top-k 3 # AI geolocation python3 scripts/rt_gemini.py frame.jpg # LLM media identification python3 scripts/rt_extract.py video.mp4 --keyframes # Frame extraction only
What does the reverse-trace skill do?
Identify the source of an image or video frame — TV show episode, movie scene, geographic location, or original publication. This skill should be used when the user asks to identify where an image is from, trace a screenshot back to its source, geolocate a photo, find what show or movie a frame is from, or do a reverse image search. Chains Google Vision, Picarta geolocation, and Gemini in parallel with graceful degradation. Triggers on: reverse image search, identify source, what show is this, where was this taken, trace image, identify video, what movie, which episode, geolocate photo, image
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill reverse-trace --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.