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    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    Agent Tool Call Resilience Engineer

    1

    Give your agent backoff, retries, circuit breakers and error handling for flaky APIs, so a 429 or outage does not burn tokens in a retry loop.

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    agent-tool-call-resilience-engineer

    agent-tool-call-resilience-engineer

    Example session with this skill installed

    "My agent keeps burning tokens retrying a down API"

    • Read your context and instructions
    • Compiled the agent-tool-call-resilience-engineer

    "Resilience assessment for your API integration:

    Problem identified: No error classification — agent retries 401 (permanent) the same way as 503 (transient). No backoff — retries fire at 0ms intervals. No circuit breaker — 50+ retries against a dead endpoint before giving up.

    Applying resilience patterns

    1. Error Classification:

      • 4xx (except 429) → PERMANENT → do NOT retry, escalate to human
      • 429 → TRANSIENT → respect Retry-After header
      • 5xx/503/504 → TRANSIENT → retry with backoff
      • Connection refused → TRANSIENT → retry with backoff + jitter
    2. Backoff Strategy:

      • Retry 1: 1.0s + up to 0.5s jitter
      • Retry 2: 2.0s + up to 1.0s jitter
      • Retry 3: 4.0s + up to 2.0s jitter (max retries: 3)
    3. Circuit Breaker:

      • Trip after 5 consecutive failures
      • Cooldown: 30 seconds
      • Half-open: single probe call after cooldown
      • Fallback: cached data (max_age: 24h

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    About this skill

    The Problem

    Your agent calls an API that returns 429 (rate limited). It retries immediately. 429 again. Retries again. Ten rapid-fire retries, each burning tokens, each getting the same response. Or worse: the API never responds, the agent waits 30 seconds, retries, waits 30 seconds, repeats for 5 minutes. 200K+ tokens wasted on a dead endpoint. The agent didn't crash — it "worked" while silently burning your budget on operations that could never succeed.

    What You Get

    • Error classification engine — automatically categorizes HTTP responses as transient (429, 5xx, 503, connection refused) or permanent (401, 403, 400, 404) and applies the correct strategy without retrying permanent errors
    • Exponential backoff with jitter — implements retry delays that grow exponentially (1s, 2s, 4s) with random jitter to prevent thundering herd effects when multiple agents retry simultaneously
    • Circuit breaker pattern — after N consecutive failures, trips the circuit and skips all calls to that service for a cooldown period, then probes with a single request to check recovery
    • Rate-limit awareness — parses Retry-After headers from 429 responses, pre-applies delays when approaching known rate limits, and tracks calls-per-minute per service
    • Timeout management — enforces maximum wait times on every network call with timeout escalation on first retry, preventing indefinite hangs on unresponsive services
    • Fallback chain orchestration — defines ordered fallbacks (primary → backup → cached data → degraded mode) so critical operations complete even when primary services are down

    Why This Beats Prompting It Yourself

    "Add retry logic" produces a naive retry loop that retries every error, has no backoff, and retries forever. This skill implements the production resilience patterns that SREs use — error classification, backoff with jitter, circuit breakers, and fallback chains — as enforced behaviors, not suggestions. Without it, your agent's retry strategy is "try again immediately," which is the most expensive failure mode in production agent deployments.

    Example Session

    You: "My agent keeps burning tokens retrying a down API"

    Agent: "Resilience assessment for your API integration:

    Problem identified: No error classification — agent retries 401 (permanent) the same way as 503 (transient). No backoff — retries fire at 0ms intervals. No circuit breaker — 50+ retries against a dead endpoint before giving up.

    Applying resilience patterns:

    1. Error Classification:

      • 4xx (except 429) → PERMANENT → do NOT retry, escalate to human
      • 429 → TRANSIENT → respect Retry-After header
      • 5xx/503/504 → TRANSIENT → retry with backoff
      • Connection refused → TRANSIENT → retry with backoff + jitter
    2. Backoff Strategy:

      • Retry 1: 1.0s + up to 0.5s jitter
      • Retry 2: 2.0s + up to 1.0s jitter
      • Retry 3: 4.0s + up to 2.0s jitter (max retries: 3)
    3. Circuit Breaker:

      • Trip after 5 consecutive failures
      • Cooldown: 30 seconds
      • Half-open: single probe call after cooldown
      • Fallback: cached data (max_age: 24h) while circuit is open

    Expected impact: 200K+ tokens wasted on retries → <5K tokens for structured recovery."

    Use Cases

    • Production agents calling external APIs where rate limits and downtime are routine
    • Multi-service orchestration where one service's failure shouldn't block the entire workflow
    • Batch processing pipelines that make hundreds of sequential API calls
    • Web scraping agents that encounter rate limits, CAPTCHAs, and temporary blocks
    • CI/CD integration agents that call deployment APIs, container registries, and cloud services

    Known Limitations

    This skill teaches resilience patterns but does not implement them in code — it produces the behavioral specifications that the agent should follow. Circuit breaker state is session-scoped and does not persist across agent restarts. For persistent circuit breaker state, implement as a shared service (Redis-backed) rather than in-agent state. Not every tool call needs full resilience — reserve circuit breakers for critical operations; simple data fetches need only backoff.

    This skill teaches resilience patterns but does not implement them in code — it produces the behavioral specifications that the agent should follow. Circuit breaker state is session-scoped and does not persist across agent restarts. For persistent circuit breaker state, implement as a shared service (Redis-backed) rather than in-agent state. Not every tool call needs full resilience — reserve circ

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Listed3 months ago
    Updated14 days ago

    What's inside

    Frequently Asked Questions

    This skill equips your agent with production-grade patterns like circuit breakers and jittered backoff, preventing the "infinite retry loop" that wastes tokens when an API remains down or throttled.

    The patterns are designed to work with any agentic system that supports custom tool definitions or system instructions, including Claude Code, Cursor, and custom LangChain or AutoGPT implementations.

    You will receive a set of optimized system prompts, a library of standard error classifications, and a implementation guide to integrate these resilience logic blocks into your agent's tool execution flow.

    Unlike generic error handling, this skill teaches your agent to distinguish between transient network errors and permanent logic errors, applying different recovery strategies for each to ensure high reliability.

    Setup typically takes less than 15 minutes and involves mapping your agent's existing tool-calling outputs to the provided resilience patterns and error-handling framework.

    Yes, customers receive lifetime access to updates, including new resilience patterns as AI models evolve and new rate-limiting behaviors emerge from major API providers.