Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurf+15 more

    Agent Failure Recovery Protocol

    by PubsProToolkit

    1

    A structured recovery framework to stop agent loops, handle malformed output, and manage autonomous error escalation.

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    See it in action

    You say

    The research agent has provided three identical empty responses in a row. Apply the recovery protocol to fix this task loop.

    Your agent does

    Failure Signal: Loop/Stalled (3x empty responses) Recovery Action: Decompose (Breaking 'Market Research' into 'Identify Competitors' and 'Feature Comparison') Circuit Breaker: 2/3 attempts used. Ledger Entry: Task failed due to broad scope; decomposed into smaller steps to bypass stall.

    What you get

    Prevent runaway token spend from infinite agent loopsDecompose complex tasks when sub-agents fail to deliver resultsMaintain a professional audit log of all autonomous system failuresRecover gracefully from malformed or off-contract agent output

    About this skill

    Self-Healing Agent Workflows

    The Agent Failure Recovery Protocol is a specialized logic layer for multi-agent systems and long-running autonomous tasks. It solves the "zombie agent" problem—where agents loop, stall, or drift off-task—by providing a structured decision-making framework for error handling. Instead of simple try/catch blocks, it implements a sophisticated recovery logic that preserves your token budget and keeps projects moving forward.

    What it does

    • Failure Classification: Instantly identifies if an agent is stalled, looping, or producing malformed output.
    • Graded Recovery Ladder: Implements a tiered response system that starts with cheap reframing before escalating to task decomposition or human intervention.
    • Circuit Breakers: Hard limits that prevent runaway loops and protect your API budget from infinite retries.
    • Audit Trails: Maintains a failure ledger to track recurring bottlenecks and improve workflow architecture over time.

    Why use this skill?

    Standard prompting leaves agents brittle; when they hit an error, they often repeat it until they hit a context limit. This skill adds a "supervisory" layer to your agent's reasoning, making it more resilient and professional. It's tool-agnostic, working with any agent that reads the SKILL.md standard, including Claude Code, Codex CLI, Cursor, VS Code Copilot, and Gemini CLI. The output is a clear, auditable log of why a failure happened and exactly how it was resolved.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Recently published to Agensi

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    Creator

    PubsProToolkit builds rigor-first skills for AI agents — they write your docs and content properly, then adversarially review them to catch what's wrong before it ships. The result: cleaner output and a hard quality gate in one toolkit. Built by a CMPP-certified, PhD medical writer who brings regulated-industry standards to developer docs, content, compliance, and research integrity.

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