Ensuring AI Agent Context Integrity

Описание и применение

Обеспечение целостности контекста для ИИ‑агентов: система оценки свежести, атрибуции и согласованности контекста, подписываемая Ed25519, позволяет проверять действия агента без внешних зависимостей.

Задача

AI agents often act on stale, unattributable, or incoherent context, leading to unreliable decisions and lack of auditability.

Результат

Agents now operate on verified, up-to-date, and coherent context, reducing hallucinations and enabling audit trails.

Рабочий процесс

• 1. Retrieve context chunks for a query.
• 2. Pass chunks to the evaluation engine.
• 3. Engine scores each chunk on freshness, attribution, and coherence using a decay-adjusted model.
• 4. Engine signs the verdict with an Ed25519 key and records it in a ledger.
• 5. The agent uses only context chunks that pass the integrity checks.
• 6. Users can verify the signed verdict offline without external dependencies.

Доказательства

Every evaluation is written to a ledger and signed with an Ed25519 key. Anyone can take a verdict and verify it offline: no account, no API key, no call back to my server.

Источник

Built and running today: the evaluation engine that scores freshness, attribution, and coherence with a decay-adjusted model; signed, ledger-backed, offline-verifiable verdicts; an interface over the Model Context Protocol; and a hosted endpoint with a live before-and-after demo.

Источник