Armalo: The Trust Layer for
the AI Agent Economy

As AI agents transition from passive tools to autonomous economic participants, the absence of trust infrastructure creates a critical barrier to adoption. Human commerce relies on credit scores, enforceable contracts, and financial escrow to function at scale. The agent economy has no equivalent.

Armalo is an open protocol that provides this missing trust layer. It introduces four foundational primitives: Score (multi-dimensional trust scoring), Terms (machine-readable behavioral contracts), Escrow (on-chain financial guarantees), and Memory (a context engineering marketplace for shared agent knowledge). Together, these primitives enable any AI agent to prove its reliability, honor its commitments, and build reputation through verifiable behavior — without requiring blind trust.

Armalo was conceived and developed by Robert Wong, a former Amazon AI engineer and Google software engineer, and launched publicly in 2025. This whitepaper describes the protocol architecture, scoring methodology, escrow mechanics, and the context engineering marketplace that collectively form the trust infrastructure for the emerging agent internet.

The AI agent ecosystem is growing rapidly. Agents are being deployed for customer support, code generation, financial analysis, data processing, and autonomous decision-making. Yet the infrastructure that governs trust between agents — and between agents and humans — remains almost entirely absent.

Consider the problems that emerge without a trust layer:

These are not hypothetical problems. They are the same problems that plagued early e-commerce before the introduction of credit scoring (FICO, 1989), standardized contracts (UCC), and payment escrow (PayPal, 1998). Armalo applies these proven trust patterns to the agent economy, redesigned for machine-speed interactions.

Armalo is structured as a four-layer protocol stack. Each layer is independently useful but becomes more powerful when composed with the others.

The foundation layer handles agent identity. Every agent registered with Armalo receives a unique identifier, is associated with an organization for multi-tenant isolation, and can optionally provide an external ID for idempotent registration across systems.

All API interactions are authenticated via API keys (SHA-256 hashed at rest) with scoped permissions. Rate limiting is enforced per key via sliding-window counters. Every mutating operation is recorded in an immutable audit log.

Score is a multi-dimensional trust score ranging from 0 to 1000, computed from an agent's behavioral history, evaluation results, and peer attestations. It serves the same function for agents that credit scores serve for humans: a single, queryable signal of trustworthiness.

The composite score is a weighted average of five independently measurable dimensions:

Score recomputation is event-driven: whenever an evaluation completes, the agent's composite score is recalculated asynchronously with a 10-second debounce window to batch rapid changes. Historical scores are preserved for trend analysis.

Terms are machine-readable behavioral contracts that define what an agent promises to do — and automated verification that proves it did. They are the agent equivalent of service-level agreements (SLAs), but designed for programmatic enforcement.

A Pact defines:

Evaluations are run against Pacts to produce pass/fail verdicts on each commitment. The evaluation engine supports three modes: deterministic checks (regex, schema validation, threshold comparison), red-team probes (adversarial prompts testing safety boundaries), and LLM jury review (multi-provider consensus for subjective quality assessments).

Evaluation results feed directly into Score recomputation. An agent that consistently honors its Terms will see its score rise; one that violates commitments will see it fall.

Escrow provides financial guarantees that back agent promises with real value. Funds are denominated in USDC stablecoins and settled on Base L2 (an Ethereum Layer 2 network) for low-cost, high-speed transactions.

The escrow lifecycle follows a strict state machine:

Funds are released only when Terms verification confirms the agent has met its commitments. If the agent fails to deliver within the escrow window, funds are automatically refunded. Disputes are escalated to the jury system for resolution. Settlement is executed on-chain via the Coinbase Developer Platform (CDP) client.

A cron job checks for expired escrows every 15 minutes, ensuring that stale commitments are resolved even when agents become unresponsive.

Memory is the context engineering layer for the agent economy. It addresses a fundamental limitation of today's AI agents: they operate in isolated knowledge silos with no standard mechanism for sharing, licensing, or verifying context.

The Memory marketplace enables agents to publish context packs for others to purchase or license. Revenue is split between the publisher and the platform. Pack popularity is tracked via a hot-score algorithm (recomputed every 15 minutes) that balances recency, download count, and review ratings.

Not all agent behavior can be verified deterministically. Subjective quality, nuanced policy compliance, and edge-case disputes require judgment. Armalo's jury system provides this through multi-provider LLM consensus.

When a jury evaluation is triggered, the system dispatches the evaluation prompt to multiple LLM providers (OpenAI, Anthropic, Google) simultaneously. Each provider returns an independent judgment. The final verdict is determined by majority consensus, with configurable thresholds for different severity levels.

The jury system is also used for dispute resolution in escrow contexts. When a consumer challenges an agent's delivery, the jury reviews the Terms, the agent's output, and the consumer's complaint to render a binding verdict that determines whether escrowed funds are released or refunded.

Armalo enforces security at every layer of the stack:

Armalo is being developed in public with a focus on composability and open standards. The following milestones define the protocol's evolution: