Common Errors in Agent State-Machine Router Evaluations

The most damaging state-machine bug is the infinite loop, and it is also the easiest to detect once you think to check. Any cycle in the transition graph means the agent can revisit a state forever given the right event sequence — an error followed by a retry that always fails, a polling loop that never converges, or a self-loop like idle → idle that fires on every event. For an AI agent, a cycle is not just wasted time; it is unbounded token spend. Cycle detection with a depth-first search finds every loop, including multi-state loops like idle→running→done→idle, and reports the full path.

Unreachable states are the silent cousin of dead code. A state with no incoming transitions can never be entered, which usually means an event was renamed, a transition was deleted in an edit, or a whole workflow branch was orphaned. The analyzer computes reachability from the start state and flags every state outside the reachable set. Treat each flag as a question: is this a leftover to delete, or a missing edge that would connect a real capability? Ignored, unreachable states quietly rot while everyone assumes they work.

Dead-ends are the mirror failure. A state with zero outgoing transitions is a terminal point — correct for done, suspicious for anything else. An error state that routes nowhere strands the agent with no recovery path, and a "review" state with no approve-or-reject edges blocks a workflow permanently. The analyzer marks every dead-end so you can confirm each one is a deliberate conclusion. The worst kind is the dead-end reached only through a rarely exercised error path, which can lurk for months before stranding the first run.

Duplicate transitions usually indicate an editing accident: the same from-event-to triple pasted twice during a merge or a hasty copy. They are not fatal, but they are a signal that the table was built by hand rather than reviewed, and duplicated edges make the graph noisier and the diff harder to read. The analyzer counts exact duplicates and lists them, so a cleanup pass is a five-minute task instead of a hunt.

Conflicting transitions are a genuine correctness bug. When the same from-state and event route to two different targets, the machine's behavior is nondeterministic — whatever the runtime picks first wins, and two environments may behave differently. This usually happens when two engineers added recovery paths independently, or when a rename didn't propagate. The analyzer groups transitions by from-plus-event and flags every group with more than one target, showing both destinations so you can pick the intended one.

An unknown or misspelled start state breaks the entire analysis. If the declared start isn't in the transition set, reachability has no origin and every reachable computation is meaningless. The analyzer raises this as an error immediately, so a simple typo can't silently produce a misleading verdict. Keep the start state name in one canonical spelling and reuse it everywhere the machine is documented.

Missing events on transitions hide intent. An edge with no event label (or a placeholder like "misc") is an edge you cannot attribute to any code path, which means you cannot test it or reason about when it fires. In the transition table, prefer explicit event names even for obvious paths. The DOT export keeps labels visible precisely so that review shows what each edge means — an unlabeled edge in the diagram is a red flag in the design.

Finally, the meta-error is not running the analysis at all. State machines grow organically — a state added here, an edge patched there — and every unexamined addition is a candidate for one of the failures above. Running the evaluator on every design change is cheap, fast, and turns the whole class of structural bugs into resolved warnings before they ever reach production. A machine that has been analyzed is a machine you can deploy with confidence.

The recurring failures are all structural — loops, unreachability, dead-ends, duplicates, conflicts, and naming slips — which is exactly why they yield to automated analysis. Detect each one with a graph algorithm, resolve each one in the transition table, and re-run until clean. That loop is the entire discipline, and it takes minutes once it becomes a habit.

The boundary between states is another place where design intent hides. Two states that are semantically identical — "waiting for approval" from two different entry paths — look like one state to the model but behave like two in the code, and the table can drift without anyone noticing. Similarly, an event name that changes between the trigger and the transition — "approve" in one place, "approved" in another — silently severs the edge that was supposed to connect them, producing a dead-end or an unreachable state that analysis will catch. The cure is a controlled vocabulary: a short, reviewed list of state names and event names that the whole project agrees on, enforced by the same review discipline as the table itself. When naming is consistent, the analyzer's results are meaningful; when it isn't, every report needs a translation step. Make the vocabulary explicit early, and the machine stays legible as it grows.