cognilateral-trust 1.2.0

Epistemic trust layer for AI agents — confidence tiers, routing, and accountability

cognilateral-trust

Epistemic trust layer for AI agents. AI that tells you when it's guessing.

pip install cognilateral-trust

Zero external dependencies. Python 3.11+.

Quick Start

from cognilateral_trust import evaluate_trust

result = evaluate_trust(0.7)
if result.should_proceed:
    perform_action()
else:
    escalate(result.accountability_record.reasons)

Confidence Tiers (C0-C9)

Tier	Name	Route
C0-C3	Unverified to Measured	basic — straight-through
C4-C6	Tested to Falsifiable	warrant_check — evidence required
C7-C9	Governance to Resilient	sovereignty_gate — full evaluation

Features

Core

• evaluate_trust() — confidence to tier to verdict (ACT/ESCALATE)
• @trust_gate — one-line trust enforcement decorator
• extract_confidence() — parse confidence from text, OpenAI, or Anthropic responses
• CalibratedTrustEngine — learning loop with JSONL persistence

Verification

• Claims extraction — factual, causal, comparative, quantitative
• Fidelity verification — word-overlap source checking
• Epistemic firewall — confidence mismatch detection (7-tier)
• Sovereignty gate — D-07 with D-05 welfare hard constraint

Network Primitives

• Trust decay — confidence attenuates across agent handoffs
• Contagion detection — track low-trust claim propagation
• Trust-weighted consensus — Bayesian composition, not majority vote
• Sovereign worker — leaf-level self-governance (D-07 at edge)
• Provenance chain — cryptographic accountability ledger

TrustBench

• Scoring — expected calibration error (ECE) measurement
• Fingerprint — radial calibration profile per model/domain
• CLI — trust-check run, trust-check fingerprint
• Leaderboard — self-contained HTML ranking

Integrations

• LangGraph — TrustNode for StateGraph + conditional edges
• CrewAI — TrustTool implementing the Tool protocol
• OpenClaw — TrustProvider for always-on agent governance
• Cognee — trust scoring on knowledge graph edges

MCP Server

Zero-install trust evaluation as an MCP tool:

uvx cognilateral-trust-mcp

Exposes trust_evaluate, trust_extract_confidence, and trust_health over stdio JSON-RPC 2.0.

Examples

See examples/ for runnable demos including a Colab notebook.

Example	Description
demo_trust_agent.py	End-to-end agent with trust gating and calibration
langgraph_trust_agent.py	LangGraph agent with trust node
crewai_trust_tool.py	CrewAI tool integration
anthropic_trust_wrapper.py	Anthropic API with trust evaluation
openai_trust_wrapper.py	OpenAI API with trust evaluation

Package Stats

Metric	Value
Modules	41
Tests	Run uv run pytest -q for current count
External dependencies	0
Python	3.11+
Version	1.1.0

License

Apache-2.0