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agentsop-bounded-loop

agentsope/SkillAlchemy ↗

From the author

Universal discipline for any LM-driven loop — agent retries, plan-act-observe, multi-agent handoffs, optimiser passes, test-fix cycles. Encodes the one rule every framework documents quietly and every team relearns expensively: the LM in the loop is NEVER a reliable terminator. Termination must be provided by an explicit counter + exit predicate + stagnation signal + escalation path that live OUTSIDE the LM's control. This is a tool- level, framework-agnostic skill. It maps onto LangGraph (recursion_limit + state counter + interrupt), CrewAI (max_iter + max_rpm + human_input), Claude / OpenAI SDKs (max_iterations + tool_use_budget), DSPy (declared evaluation budget), Aider (REPL + explicit retry cap), and AutoGen (max_consecutive_auto_reply). Search keywords: infinite loop, recursion limit, recursion_limit, GraphRecursionError, max iterations, max_iter, agent stuck, agent won't stop, runaway agent, ReAct loop not terminating, agent repeating itself.

Install

npx skills add agentsope/SkillAlchemy --skill agentsop-bounded-loop -a claude-code

Installs to .claude/skills/agentsop-bounded-loop/ · Each command fetches the skill straight from GitHub with the open skills CLI.

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Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.

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Why 86

Security100
Provenance72
Maintenance100
Licence100
Adoption44

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