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Card Lifecycle & Policy Intelligence (CLPI)

CLPI is Mnemom’s governance layer — a 5-phase system that transforms alignment cards from static declarations into lifecycle-managed artifacts with policy enforcement, trust recovery, risk intelligence, and on-chain anchoring.

The problem CLPI solves

Without CLPI, a common failure mode undermines trust scores:
  1. An operator adds a new MCP server to an agent (e.g., a browser tool)
  2. The alignment card is not updated to declare the new capability
  3. The agent uses the tool correctly, but the policy engine flags it as an UNMAPPED_TOOL violation
  4. The agent’s trust score drops — even though the agent did nothing wrong
This is configuration drift: the card falls out of sync with the agent’s actual capabilities. The result is false violations, unfair score declines, and eroded trust in the scoring system itself. CLPI fixes this by distinguishing configuration errors from behavioral failures, enabling trust recovery when the card was wrong, and providing governance-as-code to prevent drift in the first place.

How CLPI relates to AAP and AIP

AAP and AIP are detection protocols — they identify misalignment and compromise. CLPI is the governance layer that prevents problems, recovers from false positives, and anchors trust on-chain.
AAPAIPCLPI
RolePost-hoc verificationReal-time integrityGovernance & recovery
CatchesBehavioral drift over timeActive attacks in progressConfiguration drift, false violations
MechanismAlignment Cards + AP-TracesThinking block analysisPolicy enforcement + reclassification
WhenAfter the agent actsWhile the agent thinksBefore, during, and after
Together: AAP and AIP detect problems. CLPI prevents them and recovers from them.

The 5 phases

1

Phase 1: Policy Engine

Governance-as-code. A declarative YAML-based DSL that bridges alignment card capabilities to concrete tool enforcement. Policies define which tools map to card capabilities, what is forbidden, and how unmapped tools are handled — evaluated in CI/CD, at the gateway, and post-action.Policy Engine concepts | Policy DSL spec | Policy CLI
2

Phase 2: Card Lifecycle & Trust Recovery

Alignment cards become lifecycle-managed artifacts with versioned amendments, violation reclassification (card_gap vs. behavior_gap), automatic score recovery, session re-proofing, and compliance export. When a violation was caused by a missing capability — not agent misbehavior — the score recovers.Card Lifecycle concepts | Trust Recovery guide
3

Phase 3: Intelligence Layer

Analytical capabilities on top of policy and reputation data. Fault line analysis identifies value conflicts across teams. Risk forecasting predicts failure modes. LLM-powered policy recommendations generate governance rules from team analysis. Transaction guardrails scope enforcement to individual operations.Intelligence API
4

Phase 4: On-Chain Verification

Immutable reputation anchoring on Base L2. Merkle roots from the integrity checkpoint tree are anchored to the MnemoMerkleAnchor contract. Reputation scores are published to the MnemoReputationRegistry. Any third party can verify an agent’s score without trusting Mnemom’s infrastructure.On-Chain Verification concepts | On-Chain guide
5

Phase 5: Observability

OpenTelemetry integration for the full governance pipeline. Policy evaluation spans, reclassification spans, and policy-aware drift detection — all exported to any OTel-compatible backend. See Observability guide and OTel attributes spec.

CLPI sub-pages

API surface

CLPI spans four API domains:
DomainPhaseOverviewKey operations
PolicyPhase 1Policy APICRUD policies, evaluate tools, resolve merged policy
ReclassificationPhase 2Reclassification APIReclassify violations, recompute scores, export compliance
IntelligencePhase 3Intelligence APIFault lines, risk forecast, policy recommendations, transactions
On-ChainPhase 4On-Chain APIAnchor roots, publish scores, verify proofs

See Also