aspirations-verify

Verify goal completion by reading relevant goal fields, performing file or state hypothesis checks, and emitting status updates to determine if the execution reached the desired end state. This workflow applies unified checks to ensure robust completion.

When goal verification checks are empty, the workflow triggers an escalation protocol to ensure robust goal completion. This prevents unverified goals from falsely passing and ensures formal validation still occurs before status updates.

Yes, successful goal verification automatically unblocks dependent goals by propagating verified outputs and updating descriptions with predecessor results. This propagates verified outputs and updates descriptions with predecessor results to maintain workflow momentum.

Manage recurring streaks for long-running aspirations by logging completion metadata during the goal verification workflow. The system updates goal status to completed and handles recurring streaks to support continuous, long-running objectives.

Hypothesis-driven goal verification supports custom state and file checks by requiring the agent to read and evaluate relevant goal fields. It applies unified checks to validate whether the execution achieved its desired end state before updating metadata.

The best way to structure AI system goal verification is using a defined set of hypothesis checks applied after execution. This formal verification approach evaluates the end state, logs metadata, and updates downstream dependencies upon success.