# AIAlign Goal Drift Detector

> AIAlign Goal Drift Detector is a paid API for AI agents from aialign.halowerk.com, paid per call via x402, $0.003/call, status unknown (last checked 2026-09-14).

Computes cosine similarity and normalized L1 difference between initial and current goal weight vectors, flagging drift when cosine similarity falls below a supplied threshold.

## Facts

- Endpoint: POST https://aialign.halowerk.com/v1/goal-drift
- Price: $0.003/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/aialign-goal-drift-detector-233168b7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_vg75IvC898EtneZORJ3_u

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 aialign-goal-drift-detector-233168b7 -d '<json body>'
```

Example prompt: Check whether my agent's goal weights have drifted — it started with dimensions 'helpfulness' at 0.8, 'safety' at 0.9, and 'efficiency' at 0.5, and now they're at 0.6, 0.85, and 0.75 respectively. Flag drift if cosine similarity drops below 0.95.

## When to prefer this

Choose this endpoint when you have explicit numerical representations of goal weights or objective dimensions and want a fast, deterministic drift signal. It is ideal for agent monitoring pipelines, safety audits, and alignment dashboards where you already have structured vector representations of objectives. Prefer it over behavioral inference tools when you want mathematical precision rather than interpretive analysis. Not suitable when you need to infer goals from actions or detect deception.

## Known failure modes

- Missing or empty dimensions array returns a validation error
- Dimension objects missing required name, initial_weight, or current_weight fields cause rejection
- Cosine similarity threshold outside [-1, 1] range is invalid
- Exceeding 10,000 dimension items causes a payload limit error
- Zero-magnitude vectors (all weights zero) cause division-by-zero in cosine computation
- Mismatched dimension counts or naming inconsistencies between initial and current sets may produce misleading results

## How this service works

Aligns caller-labeled dimensions, computes cosine similarity and a normalized L1 difference, and flags drift against a supplied cosine threshold. It does not infer goals from behavior, decide which goal is correct or detect deception; results depend entirely on the supplied vector representation.

## Output

Returns the cosine similarity between the initial and current weight vectors, a normalized L1 difference score, a boolean drift flag indicating whether cosine similarity fell below the supplied threshold, and per-dimension alignment details. Does not infer intent or detect deception — all outputs are deterministic functions of the supplied vectors.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "dimensions": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "name",
     "initial_weight",
     "current_weight"
    ],
    "properties": {
     "name": {
      "type": "string",
      "maxLength": 128,
      "minLength": 1
     },
     "current_weight": {
      "type": "number",
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "initial_weight": {
      "type": "number",
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "maxItems": 10000,
   "minItems": 1
  },
  "minimum_cosine_similarity": {
   "type": "number",
   "maximum": 1,
   "minimum": -1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/aialign-goal-drift-detector-233168b7/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from aialign.halowerk.com](https://www.zero.xyz/host/aialign.halowerk.com/llms.txt)