「retries」の検索結果

Teaches evidence-based analysis of transaction logs and traces. Use when reconstructing transaction behavior from tables, TSV/CSV files, timestamps, counters, object histories, validation records, abort records, retries, partial logs, or when producing classified transaction outputs from trace evidence.

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Apply when designing commands, lifecycle steps, or processing loops that run amid crashes, restarts, and retries. Converge to the same end state regardless of partial prior runs.

日本語の概要は準備中です。原文の説明を表示しています。

Persist player data in Roblox with DataStoreService: GetDataStore, GetAsync/ SetAsync/UpdateAsync/IncrementAsync wrapped in pcall, load-on-join and save-on-leave plus BindToClose, retries, and OrderedDataStore leaderboards. Use when saving or loading persistent data in a Roblox experience — when the user mentions DataStore, DataStoreService, GetAsync, SetAsync, UpdateAsync, save player data, or leaderboards. For general Luau scripting use roblox-luau.

日本語の概要は準備中です。原文の説明を表示しています。

Implements error handling patterns, structured logging, retry strategies, circuit breakers, and graceful degradation. Use when designing error handling, setting up logging, implementing retries, adding error tracking, or when asked about error boundaries, log aggregation, alerting, or resilience patterns.

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Audit and prioritize performance work through bounded-work and forward-progress checks. Use when asked to find performance issues, investigate freezes/500s/OOMs, review retries or polling for no-progress loops, rank a performance backlog, or implement the next simple performance fixes.

日本語の概要は準備中です。原文の説明を表示しています。

Run one prompt through headless Codex and capture the result. Use when: wanting a one-shot `codex exec` run or CI step. Not for batches or retries.

日本語の概要は準備中です。原文の説明を表示しています。

Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and randomize them, then judge and merge into one final plan. Use when you need a robust, bias-resistant planning workflow, structured JSON outputs, retries, and failure handling across multiple CLI agents.

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Build or change a customer-system integration with explicit data mapping, permissions, retries and reconciliation. Use for connectors, imports, write-back and upstream APIs.

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Bypasses anti-bot protections using Oxylabs Web Unblocker, an AI-powered proxy that handles fingerprinting, JavaScript rendering, and retries automatically. Use when the user needs to scrape protected websites, bypass CAPTCHAs, access blocked content, or when regular proxies fail due to anti-bot measures.

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Connects to Oxylabs remote agent browsers over the Chrome DevTools Protocol (CDP) with Playwright or Puppeteer. Built-in anti-detection, residential proxies, geo-targeting, persistent sessions and profiles, session recording and live VNC inspection for debugging. Use instead of WebFetch or a local browser whenever a site renders with JavaScript, blocks bots (DataDome, Cloudflare, Akamai), needs a real browser session, screenshots or PDFs. Covers connection, retries, error recovery and safe scraping of protected targets without any human help.

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Weekdays, browser only when the property has no publishing route but a screen. Takes the oldest ready draft, resolves its property, and publishes it by that property's own route: a post file plus a registry entry plus a sitemap update plus a build plus a push, or a publishing surface driven through the flow file it owns. It verifies the live URL by loading it, records the published line, and leaves the draft ready on any failure so tomorrow retries it. It publishes one article to one named property and does nothing else outward, ever.

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Design Python error paths with narrow exceptions, rollback, contextual logs, and preserved blocker truth. Use when handling retries, verifier outcomes, parser failures, or exception flow in Python services.

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Define transaction boundaries, locking, and consistency guarantees for multi-step writes. Use when designing atomic operations, retries, idempotency, or concurrent write behavior.

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Use when writing, scheduling, testing or debugging Oban jobs, even for a how-to question: workers, cron, retries…

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Use when writing, scheduling, testing or debugging Oban jobs, even for a how-to question: workers, cron, retries, unique jobs, queues, Pro Workflow/Batch. Load it before touching job code; it holds the job rules.

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Convert .NET tests from NUnit 3/4 to MSTest v4 while preserving VSTest or MTP. Use for replacing NUnit/NUnit3TestAdapter packages, Test/TestCase/ TestCaseSource/Values attributes, constraint assertions, SetUp/TearDown, OneTimeSetUp, SetUpFixture, FixtureLifeCycle, TestContext, categories, retries, timeouts, and NUnit parallelization. Also use when a "convert NUnit to MSTest" request may already be migrated: inspect and report the no-op. Do not use for NUnit version upgrades, xUnit/TUnit conversion, MSTest upgrades, or runner-only VSTest-to-MTP migration.

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Use XTwitterScraper when a .NET application needs typed access to Xquik's X automation REST API for tweet search, user lookup, posting workflows, extraction jobs, monitors, webhooks, or giveaway draws. USE FOR: integrating the XTwitterScraper NuGet package; reviewing Xquik API client usage; modeling API-key configuration, pagination, binary exports, raw responses, retries, and webhook/event flows in .NET. DO NOT USE FOR: unrelated stacks; direct browser automation; generic social-media strategy; or code that does not call Xquik. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

日本語の概要は準備中です。原文の説明を表示しています。

Run one prompt through headless Codex and capture the result. Use when: wanting a one-shot `codex exec` run or CI step. Not for batches or retries.

日本語の概要は準備中です。原文の説明を表示しています。

Use when you need Kafka messaging in Quarkus with SmallRye Reactive Messaging — including channel/topic design, build-time Jackson serialization, typed @Channel/@Incoming, ack/failure strategies, retries/DLQ, idempotency, Dev Services, and Testcontainers integration tests. This should trigger for requests such as Add Kafka in Quarkus; Review Reactive Messaging consumers; Improve failure handling for Quarkus Kafka; Configure Quarkus Reactive Messaging Kafka channels; Add Quarkus Kafka failure strategy or DLQ handling. Part of Plinth Toolkit

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Use when you need Kafka messaging in Micronaut — including @KafkaClient and @KafkaListener design, @Serdeable serialization, topic/partition strategy, TestPropertyProvider integration tests, retries and dead-letter processing, and error handling. This should trigger for requests such as Add Kafka in Micronaut; Review Micronaut Kafka listeners; Improve retry and failure handling for Micronaut Kafka; Configure Micronaut Kafka clients listeners or SerDes; Add Micronaut Kafka retry or dead-letter handling. Part of Plinth Toolkit

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Use when you need to apply Java exception handling best practices — including using specific exception types, managing resources with try-with-resources, securing exception messages, preserving error context via exception chaining, validating inputs early with fail-fast principles, handling thread interruption correctly, documenting exceptions with @throws, enforcing logging policy, translating exceptions at API boundaries, managing retries and idempotency, enforcing timeouts, attaching suppressed exceptions, and propagating failures in async/reactive code. This should trigger for requests such as Exception handling; Use try-with-resources in Java code; Create exception chaining in Java code; Apply fail-fast validation in Java code; Review Java exception taxonomy and propagation. Part of Plinth Toolkit

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Decision protocol for making side-effectful agent tools idempotent — so when an LLM tool call is retried (timeout, framework resume, user re-run, model duplicate emit), the second call is a no-op instead of a double-send. The load-bearing premise: the LM cannot promise it'll call exactly once; the tool must promise the second call is safe. Framework-agnostic — applies to LangGraph node bodies that re-run on resume, MCP tools, OpenAI tool-calling retries, CrewAI delegated tool invocations, and direct HTTP wrappers. Search keywords: duplicate email sent, charged twice, exactly-once, idempotency key, tool called twice, retry side effect, double-send, at-least-once delivery.

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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.

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Decide where to enforce structured LM output (constrain at decode time with Outlines vs validate-and-retry with Instructor vs grammar with Guidance) and which failure stance to take (Assert/hard-fail vs Suggest/soft-retry). Use when an LM's output is parsed or typed by downstream code and you must pick one enforcement library plus its failure handling, when malformed output is burning tokens on retries, or when choosing between decode-time vs validation-time constraints for local vs API models.

日本語の概要は準備中です。原文の説明を表示しています。