agent-loop-guard

Framework-agnostic agent loop detection — sliding window similarity scoring to catch stuck agents.

Install

pip install agent-loop-guard

Quick Start

from loop_guard import LoopGuard, Action

guard = LoopGuard()

for action in agent_actions:
    decision = guard.check(tool=action.name, args=action.args)
    if decision.action == Action.STOP:
        print(f"Loop detected: {decision.reason}")
        break

Why not just max_iter?

Approach	What it catches	Limitation
max_iter=10	Runaway agents	Kills long legitimate tasks; misses 3-step loops at step 9
agent-loop-guard	Exact repeats, fuzzy repeats, A→B→C→A cycles, output stagnation	—

max_iter is a blunt timeout. agent-loop-guard detects behavioral patterns — the agent doing the same thing over and over, even with slight variations.

Detection Strategies

Strategy	What it detects	Confidence signal
Exact Repeat	Same (tool, args) called repeatedly	Consecutive identical calls
Fuzzy Repeat	Near-identical args (Jaccard + edit distance)	Similarity > threshold
Cycle Detection	A→B→C→A→B→C repeating sequences	Pattern repetition count
Output Stagnation	Tool returns same output repeatedly	Output similarity > threshold

All four strategies run on every call. The highest confidence wins.

API

guard = LoopGuard(
    window_size=10,             # actions to keep in memory
    similarity_threshold=0.85,  # fuzzy match threshold
)

decision = guard.check(
    tool="web_search",          # tool/function name
    args={"query": "python"},   # arguments (dict or str)
    output="Results: ...",      # optional: enables stagnation detection
)

decision.action       # Action.CONTINUE | WARN | STOP | ESCALATE
decision.reason       # "Cycle detected: [search → parse → search] repeated 3 times"
decision.strategy     # "cycle_detection"
decision.confidence   # 0.0 ~ 1.0
decision.is_loop      # True if STOP or ESCALATE
decision.should_warn  # True if WARN

guard.reset()         # reuse for next session

Action Escalation

Actions escalate with consecutive detections:

from loop_guard import ActionConfig

config = ActionConfig(
    warn_threshold=2,      # 2 consecutive hits → WARN
    stop_threshold=4,      # 4 consecutive hits → STOP
    escalate_threshold=6,  # 6 consecutive hits → ESCALATE
)

guard = LoopGuard(action_config=config)

Generic Callback

from loop_guard.integrations.generic import LoopGuardCallback

callback = LoopGuardCallback(
    on_warn=lambda d: logger.warning(f"Loop warning: {d.reason}"),
    on_stop=lambda d: raise_stop_error(d),
)

# In your agent loop:
decision = callback.before_tool_call("search", {"query": "test"})

License

MIT