Decision Engine

The BaseCred Decision Engine determines if an identity should be allowed to perform an action based on their reputation signals. It is designed to be deterministic, context-aware, and explainable.

"Should this identity be allowed to do this action, right now?"

BaseCred is not a scoring product. It is a Decision Engine that helps platforms answer access control questions with deterministic, explainable decisions.

Core Philosophy

1. BaseCred does not create new scores — Never invents or owns a proprietary reputation score.
2. BaseCred aggregates existing reputation systems — Ethos, Talent Protocol, Neynar are first-class providers.
3. Decisions over scores — Scores are inputs. Decisions are the product.
4. Deterministic core — Same inputs → same decision. Always reproducible.
5. Context-aware — Decisions depend on where the action happens.
6. Explainable by default — Every decision produces a human-readable reason.
7. Temporal first-class citizen — Freshness matters more than absolute values.
8. AI is assistive, never authoritative — Rules decide. AI explains.

What the Engine Produces

• Decision: ALLOW, DENY, or ALLOW_WITH_LIMITS.
• Confidence: VERY_HIGH, HIGH, MEDIUM, or LOW.
• Rule IDs and explain (human-readable reasons).

Contexts

Decisions are always made within a specific context.

Context	Purpose
allowlist.general	General gatekeeping for access.
comment	Permission to post comments.
publish	Permission to publish new content.
apply	Permission to submit applications/grants.
governance.vote	Eligibility to participate in voting.

For full context definitions and parameters used to measure each context, see Foundation → Policy → Context and Decision Scenarios.

Policy Hashes

Policy hashes are the canonical identifiers for rule thresholds used by ZK flows. You can retrieve the current hashes via the interface endpoint:

• GET /api/v1/policies

Each response item includes context, policyHash, and normalizationVersion.

Documentation Map

Page	Content
Signals	Normalized signals, providers, and normalization thresholds.
Tiers & Capabilities	Tier and capability types and comparison helpers.
Rules	Rule model, evaluation order, and full rule catalog (5 phases).
Decision Output	Response shape, confidence mapping, constraints reference.
API Reference	decide(signals, context), GET/POST endpoints, response example.

Guiding Principle

If a feature does not help answer "yes or no", it does not belong in the Decision Engine.