Agent skill · research science · aiskillstore
is-this-photo-real
Verify whether an image or video is authentic, original and correctly captioned — provenance checks, error level analysis, noise and JPEG compression analysis, clone and copy-move detection, lighting and shadow consistency, C2PA Content Credentials, deepfake and AI-generation tells, and the honest limits of AI-detector tools. Use when fact-checking a photo or video, checking for a deepfake or AI-generated image, spotting manipulation, or testing whether footage is recycled or miscaptioned. Applies to KYC and onboarding fraud, insurance claim review, disinformation analysis, and evidence admissibility. Reference at useosint.com/skills/is-this-photo-real.
Why this skill is useful
Provides domain-specific knowledge on image and video verification techniques that the AI wouldn't reliably generate on its own.
What it needs
About 9k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Is this photo real Verification order is the whole skill: provenance first, pixels last. Finding the earliest copy and reading its caption settles more cases than every forensic filter combined, and it produces evidence you can show someone. Pixel forensics produces a colourful heatmap and an argument. The beginner mistake is running error level analysis on a downloaded JPEG and announcing the image is fake. The second is looking for deepfakes: the overwhelming majority of deceptive media is real footage with a false caption — right pixels, wrong war, wrong year, wrong country. Triage: what question are you actually answering The claim under test Do this first Not this --- --- --- "This shows event X in place Y" find-the-original-image, then geolocate-from-pixels Any forensic filter. Recontextualisation leaves no pixel trace at all. "This is an unaltered photograph" Signal-level analysis, on the least-processed copy you can obtain Analysing a screenshot or a platform download; both destroy the signal. "This person said this on video" Provenance, then audio-visual consistency, then face-boundary behaviour frame by frame An AI-detector score. "This image was AI-generated" Absent camera physics and incoherent object structure A detector verdict on its own. "This screenshot is genuine" Layout, font and interface-version consistency; the underlying record if one exists Image forensics. Fabricated screenshots are made in a browser, not an image editor. Then always ask what the image would look like if the claim were true, write it down, and check for those things specifically. Verification tests a hypothesis; hunting for anomalies fails, because anomalies are everywhere. Method 1. Get the best copy. Every re-encode, resize and screenshot destroys forensic signal. Chase the original upload or the agency version, not the platform rendition. Hash it, work on copies. If all you have is a screenshot, say so and lower every downstream conclusion. 2. Provenance. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/is-this-photo-real