Resemble Detect — Deepfake Detection & Media Safety

Analyze audio, image, video, and text for synthetic manipulation, AI-generated content, watermarks, speaker identity, and media intelligence using the Resemble AI platform.

Core Principle — THE IRON LAW

"NEVER DECLARE MEDIA AS REAL OR FAKE WITHOUT A COMPLETED DETECTION RESULT."

Do not guess, infer, or speculate about media authenticity. Every authenticity claim must be backed by a completed Resemble detect job with a returned label, score, and status: "completed". If the detection is still processing, wait. If it failed, say so — do not substitute your own judgment.

When to Use

Use this skill whenever the user's request involves any of these:

Checking if audio, video, image, or text is AI-generated or manipulated
Detecting deepfakes in any media format
Verifying media authenticity or provenance
Identifying which AI platform synthesized audio (source tracing)
Applying or detecting watermarks on media
Analyzing media for speaker info, emotion, transcription, or misinformation
Asking natural-language questions about detection results
Matching or verifying speaker identity against known voice profiles
Detecting AI-generated or machine-written text
Any mention of: "deepfake", "fake detection", "synthetic media", "voice verification", "watermark", "media forensics", "authenticity check", "source tracing", "is this real", "AI-written text", "text detection"

Do NOT use for text-to-speech generation, voice cloning, or speech-to-text transcription — those are separate Resemble capabilities.

Capability Decision Tree

User wants to...	Use this	API endpoint
Check if media is AI-generated / deepfake	Deepfake Detection	`POST /detect`
Know which AI platform made fake audio	Audio Source Tracing	`POST /detect` with flag
Get speaker info, emotion, transcription from media	Intelligence	`POST /intelligence`
Ask questions about a completed detection	Detect Intelligence	`POST /detects/{uuid}/intelligence`
Apply an invisible watermark to media	Watermark Apply	`POST /watermark/apply`
Check if media contains a watermark	Watermark Detect	`POST /watermark/detect`
Verify a speaker's identity against known profiles	Identity Search	`POST /identity/search`
Check if text is AI-generated	Text Detection	`POST /text_detect`
Create a voice identity profile for future matching	Identity Create	`POST /identity`

When multiple capabilities apply (e.g., user wants deepfake detection AND intelligence), combine them in a single POST /detect call using the intelligence: true flag rather than making separate requests.

Required Setup

API Key: Bearer token from the Resemble AI dashboard
Base URL: https://app.resemble.ai/api/v2
Auth Header: Authorization: Bearer <RESEMBLE_API_KEY>
Media Requirement: All media must be at a publicly accessible HTTPS URL

If the user provides a local file path instead of a URL, inform them the file must be hosted at a public HTTPS URL first. Do not attempt to upload local files to the API.

MCP Tools Available

When the Resemble MCP server is connected, use these tools instead of raw API calls:

Tool	Purpose
`resemble_docs_lookup`	Get comprehensive docs for any detect sub-topic
`resemble_search`	Search across all documentation
`resemble_api_endpoint`	Get exact OpenAPI spec for any endpoint
`resemble_api_search`	Find endpoints by keyword
`resemble_get_page`	Read specific documentation pages
`resemble_list_topics`	List all available topics

Tool usage pattern: Use resemble_docs_lookup with topic "detect" to get the full picture, then resemble_api_endpoint for exact request/response schemas before making API calls.

Phase 1: Deepfake Detection

The core capability. Submit any audio, image, or video for AI-generated content analysis.

Submit a Detection

POST /detect
Content-Type: application/json
Authorization: Bearer <API_KEY>

{
  "url": "https://example.com/media.mp4",
  "visualize": true,
  "intelligence": true,
  "audio_source_tracing": true
}

Parameters:

Parameter	Type	Required	Description
`url`	string	Yes	HTTPS URL to audio, image, or video file
`callback_url`	string	No	Webhook URL for async completion notification
`visualize`	boolean	No	Generate heatmap/visualization artifacts
`intelligence`	boolean	No	Run multimodal intelligence analysis alongside detection
`audio_source_tracing`	boolean	No	Identify which AI platform synthesized fake audio
`frame_length`	integer	No	Audio/video analysis window size in seconds (1–4, default 2)
`start_region`	number	No	Start of segment to analyze (seconds)
`end_region`	number	No	End of segment to analyze (seconds)
`model_types`	string	No	`"image"` or `"talking_head"` (for face-swap detection)
`use_reverse_search`	boolean	No	Enable reverse image search (image only)
`use_ood_detector`	boolean	No	Enable out-of-distribution detection
`zero_retention_mode`	boolean	No	Auto-delete media after detection completes

Supported formats:

Audio: WAV, MP3, OGG, M4A, FLAC
Video: MP4, MOV, AVI, WMV
Image: JPG, PNG, GIF, WEBP

Poll for Results

Detection is asynchronous. Poll GET /detect/{uuid} until status is "completed" or "failed".

GET /detect/{uuid}
Authorization: Bearer <API_KEY>

Polling best practice: Start at 2s intervals, back off to 5s, then 10s. Most detections complete within 10–60 seconds depending on media length.

Reading Results by Media Type

Audio results — in metrics:

{
  "label": "fake",
  "score": ["0.92", "0.88", "0.95"],
  "consistency": "0.91",
  "aggregated_score": "0.92",
  "image": "https://..."
}

label: "fake" or "real" — the verdict
score: Per-chunk prediction scores (array)
aggregated_score: Overall confidence (0.0–1.0, higher = more likely synthetic)
consistency: How consistent the prediction is across chunks
image: Visualization heatmap URL (if visualize: true)

Image results — in image_metrics:

{
  "type": "ImageAnalysis",
  "label": "fake",
  "score": 0.87,
  "image": "https://...",
  "ifl": { "score": 0.82, "heatmap": "https://..." },
  "reverse_image_search_sources": [
    { "url": "...", "title": "...", "verdict": "known_fake", "similarity": 0.95 }
  ]
}

label / score: Verdict and confidence
ifl: Invisible Frequency Layer analysis with heatmap
reverse_image_search_sources: Known sources found online (if use_reverse_search: true)

Video results — in video_metrics:

{
  "label": "fake",
  "score": 0.89,
  "certainty": 0.91,

resemble-detect