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ForgeMesh GitHub Signal Intelligence — Sequence Anomaly Detection
x402
ForgeMesh GitHub Signal Intelligence — Sequence Anomaly Detection is a paid API for AI agents from anomaly.forgemesh.io, paid per call via x402, $0.03/call, status unknown (last checked 2026-09-14).
Analyzes a GitHub repository's event sequences using NASA-derived algorithms to detect anomalies, bot activity, novelty signals, and coordinated activity patterns
Price / call$0.03
Success—
StatusUnknown
How this service works
Watch a GitHub repo's activity stream for anomalous patterns — commit bursts, force pushes, issue floods, merge rushes, bot takeovers
Output
Returns a JSON object containing: the repo name, a human-readable story label (e.g. 'Merge Sprint'), a novelty rating (low/medium/high), bot ratio (0–1), a sequence score (integer), total event count, unique actor count, a peak window array of recent event types, and a breakdown of event types (PR_OPEN, PR_MERGE, ISSUE_OPEN, COMMIT_PUSH, etc.).
Example use cases
Detect coordinated activity in security fork
“I'm investigating a fork of a major security library that popped up last week. Can you scan its GitHub activity and tell me if there's coordinated bot behavior or if multiple accounts are pushing changes in sync?”
Monitor open source project health
“We're considering contributing to this new Node.js middleware library, but I want to make sure the repo isn't being flooded by bots. Can you analyze the recent activity and give me a bot ratio and novelty score?”
Identify suspicious merge campaign patterns
“Our security team flagged a repository for unusual activity. Can you run an anomaly detection on it and tell me if there's a merge sprint happening, any weird event sequences, or signs of coordinated actors trying to slip code in?”
Technical details
Endpoint
POSThttps://anomaly.forgemesh.io/api/github-watchWhen to prefer
Use this endpoint when you need real-time sequence anomaly detection on a specific GitHub repository — particularly when investigating bot activity, coordinated merge campaigns, unusual contributor patterns, or novelty signals in open source projects. Prefer this over generic GitHub API calls when you want a pre-scored, narrative-labeled intelligence summary rather than raw event data.
Side effects
- Invalid or non-existent repo format returns an error
- Private repositories may not be accessible or return empty results
- Rate limiting or payment failure (x402 micropayment not processed) blocks the request
- Repos with very low activity may return low-confidence scores
- Missing required 'input' object returns schema validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| repo | string | GitHub repo in owner/repo format, e.g. vercel/ai |
Output
Schema · Response
{
"type": "json",
"example": {
"repo": "vercel/ai",
"story": "Merge Sprint",
"domain": "github",
"novelty": "medium",
"bot_ratio": 0.15,
"peak_window": [
"PR_MERGE",
"PR_MERGE",
"COMMIT_PUSH",
"PR_MERGE",
"MERGE_RUSH"
],
"total_events": 87,
"unique_actors": 12,
"sequence_score": 52,
"event_breakdown": {
"PR_OPEN": 8,
"PR_MERGE": 12,
"ISSUE_OPEN": 5,
"COMMIT_PUSH": 30
}
}
}Tags
x402
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