「failures」の検索結果

Debug complex Claude API issues including context window overflow, tool use failures, streaming corruption, and response quality problems. Trigger with phrases like "anthropic advanced debug", "claude complex issue", "claude tool use failing", "claude context overflow".

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。

Classify Alchemy authentication, JSON-RPC, Data API, throughput, and partial-response failures before applying bounded recovery. Use when an Alchemy integration fails or degrades. Trigger with "Alchemy error", "Alchemy 429", or "debug an Alchemy request".

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 Algolia request, credential, index, task, and query failures from concrete evidence. Use when an integration returns 4xx or 5xx responses, stale results, or unexpected empty hits. Trigger with "debug Algolia error", "Algolia 403", or "Algolia search failed".

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。

Isolate complex Adobe failures across DNS/TLS, auth, entitlement, schema, async state, storage, Runtime, and downstream layers without leaking credentials or content. Use when the task requires adobe layered failure isolation. Trigger with "deep debug Adobe", "Adobe job stuck", or "Adobe intermittent failure".

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。

Classify Adobe failures from redacted response evidence and select the smallest bounded recovery. Use across auth, Firefly, Photoshop, PDF Services, Events, and App Builder. Use when the task requires adobe response-led error triage. Trigger with "fix Adobe error", "Adobe 403", or "Adobe API failed".

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。

Triage Abridge recording, note-review, Epic handoff, and access failures from observed evidence without inventing vendor error codes. Use when an Abridge clinical workflow is degraded. Trigger with "diagnose this Abridge 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。

Use when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).

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。

Monitor a PR's CI checks and Greptile code review after submission. Polls CI status, auto-fixes failures via ralph-loop, waits for Greptile review, addresses comments, and iterates until green.

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。

Guides work on the Figma I/O package (@grida/io-figma, packages/grida-canvas-io-figma/). Covers the fig-kiwi binary parser, Kiwi→REST→Grida conversion pipeline, fig2grida CLI, REST API JSON conversion, and testing with clipboard/fig/REST fixtures. Use when adding node type support, fixing conversion bugs, extending fig2grida, working on the fig-kiwi parser, writing tests for Figma import, or debugging clipboard paste failures after a Figma update.

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 production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "deployment pipeline", "chaos engineering", "retry storm", "health checks", "my service keeps crashing", "prevent cascading failures", or "make it resilient". Also trigger when designing resilient microservices, planning zero-downtime deployments, or capacity-planning for peak load. Covers stability patterns, capacity planning, deploy/release decoupling, and observability. For data systems, see ddia-systems. For system architecture, see system-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。

Design products and pricing around validated willingness to pay, from Ramanujam & Tacke's "Monetizing Innovation". Use when the user mentions "pricing", "how much should we charge", "willingness to pay", "pricing page", "packaging", "freemium vs free trial", "are we leaving money on the table", "nobody buys at this price", "price increase", or "good-better-best". Also trigger when designing or auditing pricing and packaging, validating willingness to pay before building, segmenting customers by value, or choosing between subscription, usage-based, and freemium models. Covers price-before-product, willingness-to-pay talks, the four failures (feature shock, minivation, hidden gem, undead), leader/filler/killer packaging, and behavioral pricing. For offers and guarantees, see hundred-million-offers. For what customers value, see jobs-to-be-done.

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。

Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.

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。

Keeps production assets available — ranking equipment by consequence of failure, setting preventive and predictive intervals, sizing spares, and moving a plant off reactive maintenance. Use this to build or fix a maintenance program, decide what to put on a PM schedule, diagnose repeat failures on one asset, justify spares inventory, or work out why a plant that maintains everything still has unplanned downtime.

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。

Owns execution: how work actually gets done across the organization, including process, program management, capacity, vendors, supply chain, and service delivery. Use this when execution is the problem rather than strategy, to design or fix a process, to resolve cross-functional handoff failures, to plan capacity, to assess delivery risk, or when the same failure keeps recurring. Also use to decide whether to build, hire, or outsource a capability.

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 and fix failing GitHub PR checks for xquic. Use when a PR, branch, or commit has failed CI, GitHub Actions, build checks, test checks, or requested validation failures that should be diagnosed from logs before editing.

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 evaluating Hindenburg-style investigative short reports: evidence chains, promoter networks, stock promotion, related parties, disclosure failures, and catalyst-driven short narratives.

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 evaluating David Einhorn-style forensic shorts and longs: accounting red flags, governance problems, capital allocation failures, and evidence-based short theses.

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 and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.

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。

Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test 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。

Use when creating or editing skills, before deployment, to verify they work under pressure and resist rationalization - applies RED-GREEN-REFACTOR cycle to process documentation by running baseline without skill, writing to address failures, iterating to close loopholes

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。

Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test 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。

Debugging specialist for errors, test failures, and unexpected behavior. Use proactively when encountering any 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。

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。