「failure」の検索結果

Operate NVIDIA DOCA Management Service (`dmsd` + `dmspe`) on a BlueField, Arm/x86 host, or Kubernetes pod: choose deployment and authentication, configure `-allowed_users` and `dmsgroup`, use gNMI Get/Set/Subscribe, run supported gNOI workflows, and debug frontend/backend failures. Trigger even without "DMS" for "manage a remote BlueField over gRPC", "gNOI reboot from orchestrator", or fleet-management requests. SAFETY: reboot, OS install, factory-reset, and managed-file deletion are destructive and require target-bound explicit confirmation; never invoke them speculatively. Route installation and library/API build questions elsewhere, and route turnkey aggregation to the externally-productized DOCA Telemetry Service.

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 this skill when the user is dealing with the DOCA environment around their workload — verifying an install is healthy, preparing the build env (pkg-config, headers, LD_LIBRARY_PATH, hugepages, devlink, representors), debugging env-class failures, deciding container-vs-bare-metal deployment shape, or reaching a DOCA install from a host that doesn't have one yet via the NGC DOCA container Stage-1 fallback. Trigger even when the user does not explicitly mention "DOCA setup" — typical implicit phrasings include "I just got a BlueField, what now", "my code is built, how do I run it", "pkg-config can't find doca-flow", "no free 2048 kB hugepages", "representor X not found", "I'm on a Mac and want to learn DOCA". Refuse and route elsewhere for library API specifics (Flow pipes, RDMA queues), the modify-a-sample first-app workflow or DOCA_ERROR_* program-side debugging, and "where is X documented" knowledge-map questions — those belong to other skills.

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。

Finds the root cause of a bug, failure or recurring problem by asking "why" until the answer is a cause you can fix. Use when the user asks why something keeps happening, or wants the root cause rather than a quick fix.

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。

[omh] Turn repeated lessons into written rules: extract repeated principles from skills, prompts, traces, reviews, and failures into reviewed rule candidates without auto-mutating guidance. Use when the user says: rules-distill, rules distill, distill rules, rule distillation, principle distill, skill principles, extract agent rules, turn traces into rules.

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。

[omh] Tracking cost, tokens, latency, or service health: prepare an operations command-board for wrapper-safe token, cost, latency, run history, queue, failure-mode, external metric-provider, and service-quality evidence boundaries. Use when the user says: ops-observability-card, observability card, operations command board, ops command board, service quality board, service quality, external metric provider, metric provider.

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。

[omh] Unsorted customer feedback and bug reports: cluster customer signals and choose the next workflow. Use when the user says: feedback-triage, customer-feedback-triage, feedback triage, customer feedback, feedback cluster, bug or feature, feature request triage, payment failure feedback.

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。

[omh] Agent is stuck, looping, or drifting: capture a stuck, looping, drifting, or repeatedly failing agent run, diagnose the likely failure pattern, and prepare the smallest safe recovery action. Use when the user says: agent-debug, agent debug, agent debugging, agent introspection, agent self-debug, self-debug, self debugging, looping agent.

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

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。

Introspect, explain, and improve Ralph Orchestrator using its published llms.txt doc map. Use this skill whenever the user asks questions about Ralph's behavior, wants to understand how a Ralph internal works (event loop, hats, memories, tasks, backends, presets), debug an unfamiliar failure mode, or propose a code change to the ralph-orchestrator repo. The skill teaches the agent to discover authoritative answers from the live docs via llms.txt before guessing, and to scope improvements through the published architecture rather than the local checkout alone.

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。

Diagnose and fix a reproducible failure in an existing project. Use for crashes, broken behavior, or failing checks, not greenfield planning.

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。

Lookup documented AKS fixes only when the prompt includes an exact catalog signature and all of its qualifiers: VMCannotFitEphemeralOSDisk; NodePoolMcVersionIncompatible; 'NodeImageVersion is not accepted'; AKS SkuNotAvailable with size, location, and zone; ZonalAllocationFailed with insufficient zone capacity; OverconstrainedAllocationRequest with listed constraints; nested AKS vmssCSE/CSE VMExtensionError_OutboundConnFail, VMExtensionError_K8SAPIServerConnFail, or VMExtensionError_K8SAPIServerDNSLookupFail; or AllocationFailed with the full cataloged internal-error or insufficient-regional-capacity message. Never use for quota errors, code-only or bare wrappers, generic symptoms, incomplete signatures, or failures outside AKS; use aks-troubleshooting or azure-diagnostics.

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。

Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke agent, agent.yaml, agent insights, pull agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, prompt optimizer, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).

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。

Assess and improve the reliability posture of PaaS Applications (Azure Functions and Azure App Service). Scans deployed resources for zone redundancy, ZRS storage, health probes, and multi-region failover. Presents a feature-pivoted checklist, then drives staged remediation (CLI or IaC patches) end-to-end with user confirmation. WHEN: "assess reliability", "check reliability", "zone redundant", "multi-region failover", "high availability", "disaster recovery", "single points of failure", "reliability posture", "resiliency".

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。

Plan, deploy, operate, and troubleshoot Azure Local (formerly Azure Stack HCI): sizing and prerequisites, Arc registration, lifecycle updates, workloads (Azure Local VMs, AKS on Azure Local, images, disks, logical networks), SDN and network security, and failure triage — starting read-only and confirming before risky changes. WHEN: Azure Local, Azure Stack HCI, Arc resource bridge, custom location, Azure Local VM, Arc VM, AKS on Azure Local, AKS hybrid, SDN, Lifecycle Manager, Azure Local update, disconnected site.

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。

Apply Michael T. Nygard-inspired production reliability rules when designing failure handling, timeouts, retries, circuit breakers, observability, or deployment 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。

Screen US stocks for Stockbee-style short-term Momentum Burst setups using 4% breakout, dollar breakout, range expansion, volume expansion, prior range contraction, close-location, failure filters, and risk-distance scoring. Use when the user asks for Stockbee, Pradeep Bonde, momentum burst, 4% breakout, range expansion, dollar breakout, short-term swing momentum candidates, or 3-5 day burst setup review.

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。

Synthesize the three Jason Shapiro contrarian-pipeline verdicts (COT crowding, news-reaction failure, weekly price-action confirmation) into one actionable setup_status via a fail-closed precedence state machine. Pure, offline synthesis -- no network, no API keys, no computation beyond validation and precedence.

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。

Memory integrity audit. Detects hallucinations, circular confirmations, and state poisoning. Runs automatically after 2 consecutive failures or at nightly deep dive. Uses Opus 4.6 as the auditor model.

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。

Guide for running, reviewing, and fixing test failures across grails-core modules using Gradle test reports

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。

Design confirmations, status updates, and notifications that tell users an action registered. Use when the system must acknowledge success or change. For waiting states use `loading-states`; for failures use `error-handling-ux`.

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 repeated, measured Git experiments toward a numeric target; keep improvements and revert failures. Use for autonomous optimization or managing an autoresearch run, not one-shot edits.

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。

Vue 3 debugging and error handling for runtime errors, warnings, async failures, and SSR/hydration issues. Use when diagnosing or fixing Vue issues.

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。

Diagnoses and resolves Amazon S3 Files issues including mount failures, permission errors, synchronization problems, and performance issues. Use when the user has an S3 file system that is not mounting, returning access denied, not syncing changes to S3, showing files in lost+found, or performing slower than expected.

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。