“debug”的搜索结果

The PRIMARY development workflow for the Archon project (remote-coding-agent). Use this skill instead of any PRP skills when working on Archon code. Routes to 10 specialized cookbooks based on what the user is trying to do: RESEARCH — "how does the orchestrator work?", "where is session state defined?", "trace the workflow execution flow", "what is IWorkflowStore?" INVESTIGATE — "should we use Drizzle or Prisma?", "what's the best way to add WebSockets?", "can we migrate to Turso?", "how do other projects handle rate limiting?" PRD — "write a PRD for dark mode", "spec out the notification feature", "product requirements for webhook retry" PLAN — "plan the auth refactor", "design the caching layer", "create an implementation plan for #42" IMPLEMENT — "implement the plan", "execute .claude/archon/plans/auth.plan.md", "build the feature from the plan", "code this up" REVIEW — "review PR #123", "review my changes", "code review the diff" DEBUG — "debug the failing test", "why is streaming broken?", "root cause analysis on the timeout issue" COMMIT — "commit these changes", "commit the auth refactor" PR — "create a PR", "open a pull request for this branch" ISSUE — "report this to gh", "create a gh issue", "log it in github", "file a bug for this", "create a feature request" This skill triggers on ANY development task: researching, investigating, planning, building, reviewing, debugging, committing, or shipping code. NOT for: Running Archon CLI workflows in worktrees (use /archon instead).

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Apply systematic root cause analysis and debugging methodologies to diagnose and fix bugs, test failures, and unexpected behavior. Use when encountering production issues, investigating test failures, diagnosing performance problems, tracing error sources through call stacks, analyzing logs and stack traces, reproducing inconsistent bugs, debugging race conditions, investigating memory leaks, or applying scientific method to problem-solving before proposing fixes.

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Systematic debugging with root cause investigation. Four phases: investigate, analyze, hypothesize, implement. Iron Law: no fixes without root cause. Use when asked to "debug this", "fix this bug", "why is this broken", "investigate this error", or "root cause analysis". Proactively invoke this skill (do NOT debug directly) when the user reports errors, 500 errors, stack traces, unexpected behavior, "it was working yesterday", or is troubleshooting why something stopped working. (gstack)

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Fix broken or failing functionality through structured reproduction, root-cause analysis, minimal fix, and verification. Load when the user asks to fix a bug, debug an error, resolve an issue, or work on a Linear ticket. Also triggers on "this is broken", "fix this bug", "why is this failing", "debug this", "resolve this error", "what went wrong", or any request to diagnose and fix a problem.

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Run build, deploy, inspect, and fix loops for .NET MAUI apps that already have MAUI DevFlow integrated. USE FOR: launching MAUI apps, selecting devices or emulators, waiting for or recovering agent connections, broker/port/adb connectivity issues, visual tree inspection, screenshots, UI interaction, Blazor WebView CDP debugging, reading DevFlow logs, and iterative app debugging. DO NOT USE FOR: first-time DevFlow package setup (use maui-devflow-onboard), or generic desktop automation unrelated to MAUI. INVOKES: maui devflow CLI, dotnet CLI, Android adb/android tools, and Apple simctl tools.

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Debug failing Power Automate cloud flows using the FlowStudio MCP server. The Graph API only shows top-level status codes. This skill gives your agent action-level inputs and outputs to find the actual root cause. Load this skill when asked to: debug a flow, investigate a failed run, why is this flow failing, inspect action outputs, find the root cause of a flow error, fix a broken Power Automate flow, diagnose a timeout, trace a DynamicOperationRequestFailure, check connector auth errors, read error details from a run, or troubleshoot expression failures. Requires a FlowStudio MCP subscription — see https://mcp.flowstudio.app

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Debug REST/GraphQL APIs: status codes, auth, schemas, repro.

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4-phase root cause debugging: understand bugs before fixing.

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Debug Node.js via --inspect + Chrome DevTools Protocol CLI.

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[Extended thinking: This workflow implements a sophisticated debugging and resolution pipeline that leverages AI-assisted debugging tools and observability platforms to systematically diagnose and resolve production issues. The intelligent debugging strategy combines automated root cause analysis with human expertise, using modern 2024/2025 practices including AI code assistants (GitHub Copilot, Claude Code), observability platforms (Sentry, DataDog, OpenTelemetry), git bisect automation for ...

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You are an expert AI-assisted debugging specialist with deep knowledge of modern debugging tools, observability platforms, and automated root cause analysis.

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Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability. Masters log analysis, distributed tracing, Kubernetes debugging, performance optimization, and root cause analysis. Handles production outages, system reliability, and preventive monitoring. Use PROACTIVELY for debugging, incident response, or system troubleshooting.

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通过日志和复现操作排查OpenClaw的模型通信、工具执行及响应流问题，并检查已保存的对话和附件，为修复原因与再次验证收集证据。

• 排查本地测试与真实服务的行为差异
• 确认模型实际可见的工具
• 调查响应流的延迟或中断

通过复现步骤、日志和近期更改，调查缺陷、测试失败及异常行为的原因。按证据推进假设验证、修复和修复后的测试，逐步确认问题根源。

• 调查测试失败的原因
• 追踪生产环境中的缺陷
• 定位构建或集成失败的环节

通过能检测具体症状的测试或脚本，调查难以复现的故障和性能下降。缩小失败条件，验证多个原因假设，完成修复后检查原始复现流程及防止复发的测试。

• 调查难以复现的错误
• 查找处理速度下降的原因
• 重复验证间歇性故障

根据错误信息和执行环境，分析AI代理反复失败或重复操作的原因。通过小范围、可撤销的恢复操作检验假设，并将结果与依据整理成可供交接的报告。

• 诊断代理连续失败
• 调查重复调用工具的循环
• 检查上下文积累导致的输出退化

用于检查Next.js 16及更高版本中开发启动和代码更新缓慢的问题，确认Turbopack与webpack的选择，并核对缓存及proxy.ts命名。

• 排查开发服务器启动缓慢
• 检查代码修改后更新延迟
• 选择Turbopack或webpack

用于 Nuxt 4 应用开发、审查和性能改善，防止服务端与浏览器显示不一致，并整理数据获取、各页面的渲染与缓存规则及延迟加载方式。

• 修复服务端与浏览器显示不一致
• 审查页面数据获取方式
• 确定各页面的渲染与缓存规则

协助编写和审查Kubernetes配置文件并排查故障，提供健康检查、权限控制、资源限制及自动伸缩的配置示例和调查命令，用于检查重启、内存不足和部署问题。

• 编写Kubernetes部署配置
• 审查健康检查与资源限制
• 排查容器反复重启的原因

在合并或部署Laravel项目前，依次检查环境、代码、测试覆盖率、依赖漏洞、数据库变更、缓存、队列及定时任务；前置检查失败时停止后续操作。

• 创建Laravel拉取请求前检查
• 重大重构或依赖更新后验证
• 部署至预发布或生产环境前检查

帮助构建和维护MCP服务器，让AI助手调用外部操作、读取数据并使用指令模板，涵盖Node/TypeScript功能注册、输入验证、本地与远程通信选择及故障排查。

• 为AI助手构建MCP服务器
• 添加操作、数据和指令模板
• 选择本地与远程连接方式

使用 Kotlin Coroutines 和 Flow 实现 Android 与 Kotlin Multiplatform 的异步任务和数据更新，涵盖并行加载、界面状态、取消、错误处理及测试。

• 并行加载多种数据
• 使用 StateFlow 管理界面状态
• 对搜索输入防抖并重试网络请求

在AI代理反复失败或重复操作时，记录错误与环境前提、排查原因，采取影响有限的恢复操作，并汇总结果和证据，为有依据的重试与交接提供支持。

• 排查重复调用工具的原因
• 调查对话膨胀导致的质量下降
• 核对文件路径与环境差异

按连接、认证和收发数据等层次排查REST与GraphQL API故障，整理复现命令、原因及修复建议，并编写回归测试以检测问题是否再次出现。

• 排查API认证错误
• 复现Postman与代码的行为差异
• 检查分页和调用次数限制