Results for “traces”

Systematically diagnose and fix software bugs by analyzing error messages, stack traces, logs, and runtime behavior across multiple languages. Use when the user requests debugging or provides relevant inputs for this workflow.

Generates a structured post-task reflection capturing surprises, patterns, prompt improvements, and gotchas, writing it to a markdown file without modifying project rules.

Track code changes with structured JSON records, an enforced state machine, and a session handoff format for AI continuity.

Craft messages that are understood, remembered, and drive action using the SUCCESs framework (Simple, Unexpected, Concrete, Credible, Emotional, Stories).

Debug and optimize AI agents by analyzing reasoning traces, context degradation, tool confusion, instruction drift, repeated task failures, and performance regressions.