ai-accountability

Cryptographic audit receipts for AI coding agents. Ed25519 + Merkle + RFC 3161 TSA. Supports Claude Code, Codex CLI & Cursor.

Local autonomous AI. 19k+ Python lines. Just values. Proactive Shell/CDP agency. NO FRAMEWORK/CRONJOB/BEHAVIORAL PROMPT. Autonomy grows where allowed.

ATLAST Protocol — The Trust Layer for the Agent Economy. Make AI agent work verifiable with Evidence Chain Protocol (ECP). Open source · MIT License · weba0.com

Append-only event kernel with Ed25519-signed Merkle checkpoints. Every AI action gets a verifiable receipt.

Generate replayable creative worlds with shaders, sound, motion timelines, and receipts.

LUMINA-30: non-binding boundary framework for preserving effective human refusal before irreversible AI consequences.

AI made a mistake. Can you prove what went wrong, and who is responsible? An open proposal for AI accountability management — lifecycle records, responsibility boundaries, tamper-evident audit trail. Not a finished answer.

Gate AI-agent actions with explicit grants, durable journals, MCP server support, and verification.

Epistemic infrastructure for AI accountability. Deterministic. Auditable. Sovereign.

Cryptographic receipt system for AI agent accountability. Tamper-evident, hash-chained receipts with Ed25519/HMAC signing.

Turn local files, git state, and Markdown claims into hash-stamped provenance receipts.

Accountability layer for multi-agent AI systems. Content-addressed, cryptographically signed claim DAGs.

AI governance framework built on three architectural principles: Commander's Intent, Observable Autonomy, and Convergence Is Silence. Defines Autonomous Reasoning Fidelity (ARF) as the target property.

Atomic Kernel Inference (AKI) SDK. Cryptographically seals every AI decision at the exact instant it occurs with PPP Triplet, coherence scoring, reputation scalar, and HumanDeltaChain. Court-admissible provenance for Phoenix agents. Stewarded by Genesis Glass Foundation. Canonical repo is: aiccountability-source/AgDR-Phoenix

Audit AI-agent sessions by comparing declared intent, action ledgers, and scope policy.

Client SDKs, framework adapters, and CI tooling for the Jiminy AI agent accountability API.

A public doctrine for treatment norms in machine-logic systems under moral uncertainty.

Turn your own material into a runnable course: FSRS spaced repetition, retrieval practice, real grading, zero dependencies. Halts hard at every graded step, so the machine never takes the test for you; every graded step leaves a re-verifiable receipt.

∈ Principle — A philosophical and institutional proposal for public authorship and responsibility in the age of AI. Foundational text with DOI (Zenodo). CC BY 4.0.

Formal reference model for authority, accountability, and evidentiary warrant in machine-initiated consequence attribution. Specification, paper, and adversarial validation record.