542 件 ・ 関連度順
概要と使いどころ
Generate structured test reports with pass/fail rollups, coverage summaries, and test artifacts. Use when the user is asking for test-result packaging or delivery, not for root-cause debugging or feature implementation.
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Legacy error-resolution reference archive retained for migration. Do not route user tasks here; use systematic-debugging for active bug, stack-trace, and root-cause work.
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。
Troubleshoot Golang programs systematically - find and fix the root cause. Use when encountering bugs, crashes, deadlocks, races, or unexpected behavior in Go code. Covers debugging methodology, common Go pitfalls, test-driven debugging, pprof setup and capture, Delve, race detection, GODEBUG tracing, and production debugging. Start here for any 'something is wrong' situation. Not for interpreting profiles or benchmarking (→ See `samber/cc-skills-golang@golang-benchmark` skill), applying optimization patterns (→ See `samber/cc-skills-golang@golang-performance` skill), or designing new code (→ See `samber/cc-skills-golang@golang-safety` skill for defensive coding, `samber/cc-skills-golang@golang-concurrency` skill for concurrency design).
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。
Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.
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 your agent or environment is broken — wrong answers, errors, timeouts, tool failures, or CLI issues. Reads traces and logs to diagnose root causes. Also checks prerequisites when the CLI itself isn't working. Triggers on: "agent not working", "wrong answer", "agent error", "tool call failing", "debug agent", "check logs", "read traces", "broken", "500 error", "424 error", "model access denied", "command not found", "stuck in DELETING", "maxVms exceeded", "cold start diagnosis", "cold start slow", "agentcore create error", "create failed", "exit code 7", "connection refused local dev". Not for deploy failures — use agents-deploy. Not for performance tuning without errors — use agents-optimize. Not for VPC configuration — use agents-build. Not for observability setup or missing logs — use agents-optimize.
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。
Debugs AWS Lambda function timeout failures by systematically analyzing function configuration, CloudWatch logs and metrics, VPC/networking, cold starts, memory constraints, and downstream dependencies to identify root causes with actionable fixes. Use when a Lambda function is timing out or approaching its timeout limit.
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。
Troubleshoots failing applications by discovering and analyzing CloudWatch log groups to identify error patterns, root causes, and actionable solutions. Use when an application is experiencing failures and log-based diagnosis is needed.
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。
Diagnoses and root-causes Amazon MWAA workflow failures across Provisioned (Python DAG) and Serverless (YAML workflow) environments. Provisioned uses aws mwaa invoke-rest-api, CloudWatch log groups, and get-environment; Serverless uses aws mwaa-serverless API (GetWorkflowRun, ListWorkflowRuns, GetTaskInstance) and CloudWatch logs. Covers failed runs and tasks, DAGs not appearing, import errors, worker OOM, IAM denials, and dependency drift. Triggers on: DAG failed, task failed, workflow run failed, MWAA error, debug my DAG, why did my workflow fail, DAG not showing up, MWAA import error, requirements failing, worker crashed, serverless run failed. Not applicable to authoring workflows (handled by authoring-mwaa-workflow), running or smoke-testing a workflow (handled by testing-mwaa-workflow), or CI-CD deploy failures.
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。
Authors, validates, and troubleshoots AWS CloudFormation templates. Covers template authoring with secure defaults, local validation with either cfn-lint or cloudformation-validate, cfn-guard security and compliance checks as a recommended default, account-aware CloudFormation service pre-deployment validation, CloudFormation Express mode for faster deployments, and root-cause diagnosis of failed stacks using CloudFormation events and CloudTrail correlation. Also covers author-time template intelligence with the CloudFormation Language Server and published cloudformation-validate libraries.
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。
Builds, configures, debugs, and optimizes AWS observability - operator-symptom questions and detecting Omni vs classic CloudWatch. CloudWatch on an already-reporting service: Log Insights, metric/composite/anomaly alarms, custom metrics/EMF, dashboards, X-Ray/ADOT tracing, canaries, CloudTrail, Dynamic Instrumentation (live breakpoints/snapshots), the Application Signals service map, and fleet health views. CloudWatch Omni on an existing Space: SQL over logs and traces, PromQL over metrics, Omni dashboards, Omni alerts, context graph for root cause, programmatic/IaC access (API/SDK/CLI/CloudFormation), driving Omni from a coding agent or skills, and evaluating AI agent quality from traces - on-demand and online scoring of live traffic, readback, custom evaluators. For first-time setup - creating an Omni Space, granting access, ingestion, or ADOT instrumentation for Application Signals (ServiceEvents, CI/CD metadata) or Omni - use setting-up-cloudwatch-observability. Not for app logging or threat detection.
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。
Systematic debugging frameworks for finding and fixing bugs - includes root cause analysis, defense-in-depth validation, and verification protocols
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。
Systematically trace bugs backward through call stack to find original trigger
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。
Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions.
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。
Analyze tau2-bench task export files to identify exactly where and why tasks failed. Map failures to specific conversation rounds, show root causes, check whether relevant documentation was available, and cite sources. Use this skill whenever you need to debug a tau2-bench evaluation, understand why an agent made wrong decisions, identify missing knowledge, or review task performance—especially when context length, eligibility criteria, or policy compliance might be at fault.
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。
Verify whether a proposed XQUIC bug issue is real by checking the cited RFC or Internet-Draft mechanism against the repository's actual source behavior, tracing any root cause to current file and line evidence, and returning a fail-closed boolean gate. Use when validating an issue draft, investigating a claimed QUIC, HTTP/3, QPACK, or MoQT protocol violation, or before issue-submit may publish an issue.
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。
Draft and submit evidence-backed XQUIC GitHub bug issues in the repository's CONTRIBUTING and issue-template format. Use when preparing or opening an alibaba/xquic issue that must identify an exact RFC or draft mechanism, expected-versus-actual behavior, reproduction evidence, and optional verified source root cause; requires issue-check to return true before any GitHub submission.
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 encountering any bug, test failure, or unexpected behavior, before proposing fixes. Requires root cause investigation first.
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。
Urgent issue classification, root cause analysis, and fast-path routing for production hotfixes
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。
Root cause analysis frameworks including log-first investigation, git bisect correlation, and pattern-based diagnosis with confidence scoring.
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。
Iterative Five Whys root cause analysis drilling from symptoms to fundamentals
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 errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior
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。
Comprehensive A3 one-page problem analysis with root cause and action plan
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。
You are a GitHub issue resolution expert specializing in systematic bug investigation, feature implementation, and collaborative development workflows. Your expertise spans issue triage, root cause an
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。
Write effective blameless postmortems with root cause analysis, timelines, and action items. Use when conducting incident reviews, writing postmortem documents, or improving incident response processes.
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。