What problem does it solve? Debugging sessions often devolve into trial-and-error changes that burn tokens and never converge. This Skill enforces a disciplined hypothesis→test→observe loop for failing tests or bugs, blocks git commits while tests are red, and caps each failing assertion at three iterations before escalating to the Architect. ## Core Features & Use Cases - Structured Debugging Cycle: One hypothesis, one targeted fix, one verification per cycle — no shotgun changes or unrelated refactors. - TASK_BUDGET Enforcement: A strict 3-iteration cap per failing assertion, tracked as explicit state, with an AI_DEBUG_BUDGET override for exceptional cases. - LOCKED State Guardrails: Forbids git add and git commit until the full test suite passes, preventing broken code from entering history. - Automatic Escalation: On BUDGET_EXHAUSTED, formats a structured A2A query with all tried hypotheses and consults the Architect via advisor-mcp before continuing. - Use Case: A test suite fails after a refactor. The Skill runs the suite, isolates the failing assertion, walks through at most three distinct hypotheses, and either returns to green or escalates with full context instead of thrashing. ## Quick Start Ask the agent to debug the currently failing tests using the ai-debug skill and follow its hypothesis-driven cycle until the suite passes or the budget is exhausted.