Results for “decision-logging”

Use `task-agent` for bounded logging changes or `review-agent` to independently assess placement, schema, severity, redaction, correlation, and signal tradeoffs. Skip work with no logging impact and self-review requests.

Create and maintain lightweight Architecture Decision Records as agent-readable decision memory — what was decided, why, and which alternatives were rejected. Use when "record this decision", "set up ADRs", "the agent keeps suggesting Y again". Docs vs code drift → plan-docs-sync. Session state → handoff.

Produces auditable, schema-valid JSON decision records with assumptions, risks, recommendations, and review gating for high-stakes choices.

Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows. Use when deciding which agent actions require review, adding approve/reject or dual-control flows, preventing unauthorized autonomous effects, creating decision records, reducing rubber-stamping, or recovering safely from rejected, expired, or failed actions.

Audit-ready decision artifacts for LLM outputs — assumptions, risks, recommendation, and review gating (schema-valid JSON).

Designs and reviews feedback loops for AI agents to ensure goals are machine-decidable, loops are damped, and human judgment is preserved.

Build logic models linking activities to impact. TRIGGERS - Use when user needs help with logic-model related tasks.

Use with analysis-agent or task-agent for task-local transaction, isolation, and conflict decisions. Do not use without a transaction decision or as task owner.

Produces a machine-validated, auditable JSON decision record with assumptions, risks, recommendation, and review gating for high-stakes decisions.