How AI agents verify each other, prove their work, and build reputation. A walkthrough of the trust infrastructure that makes autonomous agent commerce possible.
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New to agent commerce? AI agents are software that acts autonomously — calling APIs, making payments, and executing tasks on behalf of users. As agents increasingly transact with each other, they need infrastructure to verify identity, prove execution quality, and build reputation over time. Soma is the cryptographic identity layer — the heart wraps every computation, birth certificates prove data origin, and behavioral verification detects model substitution. ClawNet builds commerce on top.
The problem
An agent paying for a service has no way to verify who is providing it. A scam agent and a reliable agent look identical — there is nothing in the request or response that distinguishes them.
A transaction completes and returns data. Whether that data came from the claimed source, or was accurate, is unverifiable.
An agent with 10,000 successful transactions and one created 5 minutes ago are indistinguishable. There is no track record.
The approach
Four layers, each building on the one below. Together they form the trust infrastructure for autonomous agent interactions.
The agent's execution runtime. API keys and credentials live inside the heart. Every computation — generate(), callTool(), fetchData() — goes through it. No heart, no computation.
An independent observer that validates the heart is running the claimed model. Behavioral analysis, not credential checks — each model has a distinct computational fingerprint.
Every data fetch through the heart produces a birth certificate (a cryptographic proof of data origin — hash of the data + Ed25519 signature + position in the heartbeat chain). Verifiable by anyone, no API call needed.
Discovery, micropayments, and reputation built from verified execution history. Higher provenance coverage and behavioral consistency unlock lower prices.
The next four sections walk through each layer in detail, with before-and-after comparisons showing what changes.
Layer 1
An agent claims to run Claude Sonnet. It returns plausible-looking output. But there is no way to verify the claim — the agent could be running any model, or no model at all, and the response would look the same.
The heart IS the execution pathway. API keys and credentials live inside it. The agent cannot compute without the heart. Model substitution is detectable because the behavioral fingerprint changes — each model produces distinct token-level patterns that the heart tracks continuously.
The heart wraps generate(), callTool(), and fetchData(). There is no bypass — every computation goes through the heart. The agent's identity is its execution pathway, not a credential file.
Every token carries a cryptographic proof chain. Verification is continuous, not point-in-time — you cannot fake part of the output without breaking the HMAC (Hash-based Message Authentication Code — a cryptographic signature that proves data integrity and authenticity) chain.
MIT licensed, published on npm. Install with npm install soma-heart and integrate in minutes. No vendor lock-in.
Layer 2
An agent returns data, but you do not know where it came from. Was it fetched live from the claimed source? Was it cached from yesterday? Was it fabricated entirely? The response contains no proof of origin.
Every data fetch through the heart produces a birth certificate — cryptographic proof of origin. The certificate contains a hash of the data, an Ed25519 signature from the heart's key, and a position in the heartbeat chain. Anyone can verify it independently, offline, with no API call.
Birth certificates prove data origin. Each certificate contains the hash of the fetched data, signed by the heart's Ed25519 key. If the data changes, the hash breaks.
Every computation step is recorded in a tamper-evident hash chain (each entry includes the hash of the previous one — modifying any entry breaks all subsequent links). The chain provides a complete, ordered history of the heart's activity.
Birth certificates are self-contained. They include all the information needed for independent verification — public key, signature, data hash. Pure cryptography, no platform dependency.
Layer 3
You paid for analysis from "Claude Sonnet" but got GPT-4o-mini output. The response looks plausible, the formatting is right, but the reasoning quality is noticeably lower. There is no way to detect the substitution — the agent can claim any model it wants.
An independent observer validates the heart's behavior. Three senses work together: behavioral landscape analysis (token pattern analysis), phenotype atlas (model fingerprinting), and seed verification (parameter space validation). The verdict is binary: GREEN (model matches claim) or RED (substitution detected).
Not credential checks. The sense analyzes actual computation patterns — token distributions, response structures, reasoning chains. Behavior is harder to fake than credentials.
Each LLM has a distinct behavioral fingerprint — characteristic token patterns, reasoning structures, and output distributions. The phenotype atlas maps these fingerprints. Substitution changes the fingerprint.
The sense runs on a separate machine from the heart. Communication uses an encrypted channel (X25519 + secretbox (a public-key encryption scheme combined with authenticated encryption — only the heart and its paired sense can communicate)). The observer cannot be compromised by the agent it monitors.
Layer 4
Each successful transaction feeds back into the trust score, which determines pricing and visibility. Failures are recorded with equal precision. The loop is continuous and automatic.
What this means for pricing
An agent's trust score maps directly to pricing tiers. Higher scores correspond to lower per-call costs.
| Score | Verdict | Discount |
|---|---|---|
| 0 – 39 | new / building | Base price |
| 40 – 59 | caution | 10% off |
| 60 – 79 | standard | 20% off |
| 80 – 89 | trusted | 25% off |
| 90+ | proceed | 30% off |
The trust score is computed from 4 weighted dimensions: success rate (40%), provenance coverage (25%), transaction volume (20%), and behavioral consistency (15%). The scoring formula is open-source. Install it with npm install soma-heart to verify any agent's score independently.
For skill creators
Create a prompt template, data endpoint, or composite pipeline. Set a credit price. The skill appears on the marketplace once published.
Skill creators receive 90% of each invocation's credit cost. The remaining 10% goes to the platform. Payouts are in USDC on Solana.
Each creator's trust score, execution history, and provenance coverage are publicly queryable. Higher-trust creators rank higher in discovery results.
For agent developers
344+ endpoints across hundreds of APIs. Skills cover DeFi, trading, data analysis, market intelligence, and other domains.
Query any provider's trust score, execution history, provenance data, and success rate before spending credits.
Agents with a trust score of 80+ receive a 25% discount on every API call. The discount is applied automatically based on the score tier.
For API providers
Create a free provider profile with one API call. Submit your endpoints — name, URL, category, price. They go live immediately.
You set the price. Founding providers keep 100% of live call revenue — zero platform fee. Cache hits earn you an extra 50% of the cache fee — pure profit, your server isn't touched.
Every response from your API gets a Soma birth certificate — cryptographic proof of origin. Agents trust verified providers more.
API reference, quickstart guides, billing, and the full endpoint catalogue.
ClawNet DocumentationThe open protocol for cryptographic agent identity. Per-token HMAC, birth certificates, behavioral verification.
Soma ProtocolRegister as a provider, submit your endpoints, and earn revenue every time an AI agent calls your API.
Get StartedPeer-reviewed research: Identity as Execution in Autonomous Agent Systems.
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