Agent action verification service comparing before/after states
Witnessed is a service that independently verifies whether an AI agent's actions actually took effect in the real world. It compares the state before and after an action to catch silent failures where the agent reports success but the intended change did not occur. This helps developers building production agents avoid incorrect assumptions and cascading errors.
Related
Article proposes property-based testing to catch agent self-fixing bugs that example-based tests miss
A Medium article argues that example-based tests fail to catch bugs that cause AI agents to endlessly 'fix' their own code in production. The author proposes property-based testing as a more robust alternative for agent reliability.
Cinchor: accountability layer for AI agents with bound-before and prove-after
Cinchor is a primitive that enforces policy on AI agents before they act and provides cryptographic proof of actions afterward. It allows teams to give agents real capabilities (e.g., moving money, shipping changes) while maintaining auditability and preventing out-of-policy actions. The system mints scoped capabilities (spend cap, allowlist, expiry) and checks every action against them, refusing violations before execution; actions are hashed, signed, and anchored append-only for later verification.
Runeward: Sandbox AI agents with policy gates
Runeward is a sandboxing tool for AI agents that enforces policy gates to restrict agent actions. It uses LLMs to interpret and enforce user-defined policies, solving the problem of unsafe or unintended agent behavior for developers building autonomous AI systems.
Developers uncover messy failure modes in paid AI agent tool-calling workflows
A developer testing AI agents that call paid tools instead of free APIs reports that real-world execution problems—like cost uncertainty, double-spends on retries, and useless results after payment—are more interesting than polished demos suggest. The post highlights practical issues such as needing cost awareness before committing, proving intent before spending, and handling payment failures gracefully.
Snitch: deterministic claim verifier for AI agent transcripts
Snitch is a tool that watches AI agent transcript files (Cursor, Claude Code, Codex, Pi, OpenCode) and verifies claims made in prose against actual evidence like tool calls, shell output, filesystem changes, git history, and session context. It uses deterministic regex patterns to extract claims and cross-references them, flagging inconsistencies. It helps developers trust their coding agents by catching when an agent's description doesn't match reality.