> ## Documentation Index
> Fetch the complete documentation index at: https://docs.precipiq.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Consequence Links: connecting AI to dollars
> A consequence link connects a decision record to the financial event it caused, recording the correlation strength, attribution method, and link type.
A consequence link is the edge between a decision and the financial event that decision caused. Links carry four fields that make the attribution actionable: which pair they connect, how strong the attribution is, how the attribution was established, and what kind of financial impact it represents. Without links, a revenue event is just revenue. With a link pointing at a decision, that revenue is attributable to an agent with a provenance trail you can show to a skeptic — or an auditor.
The ledger records both automatic links created by the attribution engine and manual links created by a human confirming a suggestion on the dashboard. The `attribution_method` field records which — so you always know whether a number came from a machine score or a human judgment.
## Shape
```json theme={null}
{
"id": "lnk_...",
"org_id": "o_...",
"decision_id": "d5e7a3b0-...",
"financial_event_id": "fev_abc",
"correlation_strength": 0.91,
"attribution_method": "ml_inferred",
"link_type": "revenue",
"notes": "attribution engine: score=0.91",
"created_at": "2026-04-16T12:40:00.000000Z",
"deleted_at": null
}
```
## Creating a link from code
```python Python theme={null}
# ``decision_id`` is a UUID string — use whichever variable your
# caller exposes (``receipt["decision_id"]`` from ``log_decision``
# in non-batched mode, or a stored id from a prior write).
pq.link_outcome(
"d5e7a3b0-0000-0000-0000-000000000001",
"fev_abc",
correlation_strength=1.0,
link_type="revenue",
notes="direct cause — pricing API response produced this charge",
)
```
```typescript TypeScript theme={null}
await pq.linkOutcome(
'd5e7a3b0-0000-0000-0000-000000000001',
'fev_abc',
{
correlationStrength: 1.0,
linkType: 'revenue',
notes: 'direct cause — pricing API response produced this charge',
},
);
```
When you create a link via the SDK with a known `decision_id` and `financial_event_id`, set `correlation_strength: 1.0` and let the `attribution_method` default to `direct`. Reserve lower correlation values for cases where you know the relationship is partial.
## Attribution methods
| Method | Who creates it | How the engine decides |
| -------------- | --------------------------- | ------------------------------------------------- |
| `manual` | Human via the dashboard | Reviewed and confirmed by a person |
| `direct` | SDK, passing a known id | Explicit caller-supplied link |
| `temporal` | Correlation worker | Time proximity and metadata overlap |
| `ml_inferred` | Attribution engine (auto) | Composite score at or above auto-link threshold |
| `ml_suggested` | Attribution engine (review) | Score in the suggested band — awaits confirmation |
The engine's scoring combines temporal decay, Jaccard metadata overlap, a Bayesian agent-pattern prior, and amount plausibility. Links with a score in the `ml_suggested` band appear in the dashboard review queue rather than being applied automatically.
### Confirming or rejecting ML-suggested links
When the attribution engine surfaces a suggested link, you confirm or reject it from the **Links** tab in the dashboard. Confirming promotes the `attribution_method` to `manual` and makes the link active. Rejecting soft-deletes the link — it is excluded from P\&L queries but remains in forensic exports so an external reviewer can see the prior suggestion was retracted.
Soft-deleted links are never hard-deleted. The audit trail is always intact, even after a rejection.
## Link types
The decision drove positive revenue — a successful upsell, a completed checkout.
The decision drove a cost you would not otherwise have incurred — extra API calls, ops labour.
The decision created legal or compliance exposure — an erroneous claim denial, a regulated miscommunication.
Attribution matters for the audit trail but the dollar sign is zero — for example, a canceled transaction.
The sign of a link's contribution to the P\&L comes from the linked event's `amount` field, not from the `link_type`. The type is metadata for filtering and reporting, not an arithmetic override. A `revenue` link to a negative-amount event will subtract from the revenue total.
`LIABILITY` and `NEUTRAL` link types are excluded from the revenue and cost sums in the AI P\&L — liability flows into the exposure column only, and neutral links are audit metadata with no P\&L effect.