# Anansi Data Anomaly Detection

> Anansi Data Anomaly Detection is a paid API for AI agents from anansidata.xyz, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-14).

Detects statistical outliers by computing z-scores on the latest move of tracked keys against their own historical baseline.

## Facts

- Endpoint: GET https://anansidata.xyz/paid/intel/anomalies
- Price: $0.05/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/anansi-data-anomaly-detection-e5cf2143
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_pn9SP9S_pzUQWg9JtBmIQ

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability anansi-data-anomaly-detection-e5cf2143
```

Example prompt: Which keys in the crypto dataset are showing statistically anomalous moves right now — I want the ones whose latest change breaks their own historical baseline by z-score.

## When to prefer this

Use this endpoint when you need to surface which specific data points have moved unusually relative to their own history — not just which are highest or lowest in absolute terms. Ideal when monitoring many keys and wanting automated statistical triage rather than manual threshold-setting. Prefer over velocity ranking when you want self-normalized deviation, not raw speed.

## Known failure modes

- Insufficient historical data for a key yields no z-score or unreliable baseline
- Invalid dataset identifier returns an error
- Keys with very low variance may produce inflated z-scores
- Network timeout for large datasets
- Payment failure via x402 protocol blocks the request

## How this service works

Statistical outliers: keys whose latest move breaks their own historical baseline (z-score). Manufactured from accumulation.

## Output

Returns a list of tracked keys whose latest value change constitutes a statistical outlier relative to that key's own historical baseline, along with z-scores quantifying the deviation severity.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method"
   ],
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "GET",
      "HEAD",
      "DELETE"
     ],
     "type": "string"
    },
    "queryParams": {
     "type": "object",
     "properties": {
      "field": {
       "type": "string",
       "description": "Numeric field present in that dataset."
      },
      "dataset": {
       "type": "string",
       "description": "Exact dataset name."
      },
      "z_threshold": {
       "type": "number",
       "default": 3,
       "description": "Std deviations from the key's own baseline required to flag."
      }
     }
    }
   }
  },
  "output": {
   "type": "object"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/anansi-data-anomaly-detection-e5cf2143/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from anansidata.xyz](https://www.zero.xyz/host/anansidata.xyz/llms.txt)