# Burned Token Fraction — Sequential Input-Change Attribution

> Burned Token Fraction — Sequential Input-Change Attribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Computes how a change in burned or issued token counts affects the reported burned token fraction, using sequential input-change attribution (waterfall analysis).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-bx-token-burned-supply-waterfall?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/burned-token-fraction-sequential-input-change-attribution-2f4b7651
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_nUdTkNMGVFYuwqgfCfSU6

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 burned-token-fraction-sequential-input-change-attribution-2f4b7651 -d '<json body>'
```

Example prompt: Run a sequential input-change attribution on the burned token fraction: before we had 100,000 burned tokens out of 2,000,000 issued, and after we have 110,000 burned tokens out of 2,200,000 issued — show me how each input change contributed to the shift in the burn ratio.

## When to prefer this

Choose this endpoint when you need to understand how specific changes in burned token count or issued token count each contributed to a shift in the overall burned token fraction — particularly when you want a sequential (waterfall-style) decomposition rather than just a simple before/after delta. It is purpose-built for tokenomics attribution analysis using deterministic calculation on caller-supplied data, with no dependency on live blockchain data.

## Known failure modes

- issued_tokens must be greater than 0 (exclusiveMinimum enforced); submitting 0 will return a validation error
- burned_tokens exceeding issued_tokens may produce a fraction greater than 1, which may be flagged or rejected
- missing required fields (burned_tokens or issued_tokens in either before or after objects) will cause a schema validation error
- values exceeding the maximum of 10^16 will be rejected
- payment failure or insufficient USDC balance will result in a 402 Payment Required response

## How this service works

Reported burned token fraction — Sequential input-change attribution: Sequential input-change attribution for Reported burned token fraction. Supplied token observations only. Deterministic calculation or caller-threshold verdict, not a live scan, safety proof or trade recommendation. Specialised preset in a shared 50-profile, 20-operation engine. 0.01 USDC includes one bounded sequential input-change attribution report.

## Output

A sequential input-change attribution (waterfall) report showing how each input variable (burned_tokens and issued_tokens) individually contributed to the change in the reported burned token fraction between the 'before' and 'after' states. Returns deterministic calculations based on the supplied token observations, not a live scan or trade recommendation.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "after": {
   "type": "object",
   "default": {
    "burned_tokens": 110000.00000000001,
    "issued_tokens": 2200000
   },
   "required": [
    "burned_tokens",
    "issued_tokens"
   ],
   "properties": {
    "burned_tokens": {
     "type": "number",
     "default": 100000,
     "maximum": 10000000000000000,
     "minimum": 0
    },
    "issued_tokens": {
     "type": "number",
     "default": 2000000,
     "maximum": 10000000000000000,
     "minimum": 0,
     "exclusiveMinimum": 0
    }
   },
   "additionalProperties": false
  },
  "before": {
   "type": "object",
   "default": {
    "burned_tokens": 100000,
    "issued_tokens": 2000000
   },
   "required": [
    "burned_tokens",
    "issued_tokens"
   ],
   "properties": {
    "burned_tokens": {
     "type": "number",
     "default": 100000,
     "maximum": 10000000000000000,
     "minimum": 0
    },
    "issued_tokens": {
     "type": "number",
     "default": 2000000,
     "maximum": 10000000000000000,
     "minimum": 0,
     "exclusiveMinimum": 0
    }
   },
   "additionalProperties": false
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/burned-token-fraction-sequential-input-change-attribution-2f4b7651/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)