aspirations-precheck

Automating pre-selection checks involves running a comprehensive precheck sequence at the start of each iteration to verify aspiration health, detect blockers, and maintain a healthy pipeline. This prevents stalled work and surfaces pipeline gaps.

Detecting unproductive cycles requires running automated phase 0 checks to identify blockers and gate readiness. When unproductive cycles are detected, the system triggers corrective investigations to keep aspirations aligned with outcomes and resolve blockers.

The best way to maintain recurring goals and prevent stalled work is to invoke automated precheck phases at the start of every iteration. This refreshes health status, resets goal statuses when needed, and surfaces high-priority investigations.

You need to run precheck phases for aspiration health and blocker resolution at the start of each iteration before goal selection. This ensures completeness, validates gate readiness, and enables automated creation of new goals when thresholds are not met.

Yes, you need working memory and pipeline meta to orchestrate precheck phases effectively. The process coordinates with guardrails, aspiration data, pipeline meta, and working memory via scripts to validate health checks and resolve blockers.

Goal selection stalls when health thresholds are not met due to unresolved blockers or incomplete pipeline readiness. Automating new goal creation requires running pre-selection checks to validate health status and trigger corrective investigations automatically.