'failure' 검색 결과

Turn a large dataset (an existing oversized Coval test set, an export of past conversations, or a CSV/JSON of cases) into a small, high-signal Coval test set by removing duplicates, identifying unique scenarios, and selecting a representative, failure-weighted subset — then bulk-loading it with no row cap. Use when the user says "I have thousands of cases", "dedupe my test set", "my test set is too big", "turn this dataset into a test set", "pick representative scenarios", or "my CSV import only kept 10 / uploaded everything".

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Doctrine for fixing TypeScript errors against generated types (database.types.ts, api-types.ts). Use when fixing tsc or type-check failures or a type-errors batch, writing supabase .rpc()/.from() calls or DB shape guards, errors mention Json/unknown/Database, or you are tempted to cast or suppress.

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Diagnostic method for any bug, failure, regression, flake, or slowdown. Use before proposing a fix: something is broken, throwing, not saving, not showing, or 'worked yesterday'; on 'debug this' or 'find the root cause'; and immediately after a fix attempt did not work.

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next/dynamic code splitting and build-graph cost; first stop for build failures. Use before lazy-loading or deferring a heavy component, adding a dynamic import, React.lazy, or ssr: false; on 'window is not defined' or a hydration mismatch; shrinking the bundle; or on 'build failed', OOM, SIGKILL, a slower build, or 'Collecting page data'.

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Create an Agent SKILL.md fallback for an existing find-XXXX finder that relies on a fragile discovery foundation — above all LLM_DECOMPILE (patterns C/D/E), which matches the decompiled shape of a predecessor function against a stored reference and breaks when a symbol is inlined or de-inlined in a way the reference does not cover. The generated fallback coexists with the preprocessor and runs only when it returns failure, recovering every target robustly by decompiling the predecessor and following the inline/de-inline boundary with semantic anchors. Use when a finder broke on a game update, or you want to durably backstop one before it does. The recipe generalizes to any finder foundation. Triggers: create agent skill fallback, add SKILL.md fallback, robust fallback for finder, backstop LLM_DECOMPILE finder, final guarantee skill

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Write content in David Dias's authentic voice. Use when Quill or any agent needs to create tweets, blog posts, emails, marketing copy, or any content that should sound like David wrote it. David's voice is personal and conversational, mixing professional insight with personal anecdotes. He shares failures openly, values community, and speaks directly to readers with honesty and warmth. Not corporate or overly polished.

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This skill should be used when the user asks to "sandboxの互換性をチェックして", "sandbox設定を確認して", "このプロジェクトでsandboxが使えるか調べて", "sandboxでコマンドが失敗する", "check sandbox compatibility", "verify sandbox settings", "sandbox is blocking my commands", or wants to ensure their development workflow works within Claude Code's sandbox restrictions — either proactively before starting work or reactively after encountering sandbox-related failures.

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Find flaky tests from CI logs — aggregates pass rates, spots intermittent failures, recommends quarantine. After multiple runs.

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Expert knowledge of Flyway database migrations in melosys-api (Oracle DB). Use when: (1) Creating new database migrations, (2) Understanding migration versioning and naming, (3) Debugging migration failures, (4) Understanding Oracle-specific SQL patterns, (5) Adding tables, columns, or indexes. Triggers: "create migration", "new Flyway migration", "add column/table/index", "Flyway error", "checksum mismatch", "ORA-00955", "ORA-02292", "ORA-01430", "migration failed", "validate failed".

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Expert knowledge of MEDL (Medlemskapsregister) integration in melosys-api. Use when: (1) Debugging MEDL period creation/update failures, (2) Understanding data mapping between domain entities and MEDL API, (3) Working with saga steps that write to MEDL (LagreMedlemsperiodeMedl, LagreLovvalgsperiodeMedl), (4) Understanding MEDL enums (PeriodestatusMedl, LovvalgMedl, DekningMedl, GrunnlagMedl), (5) Troubleshooting Article 13 provisional vs final period logic.

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Expert knowledge of vedtak (verdict) processing in melosys-api using the saksflyt saga pattern. Use when: (1) Debugging vedtak-related issues or failures in IVERKSETT_VEDTAK_* processes, (2) Investigating race conditions where vedtak fails due to concurrent operations, (3) Understanding how fattVedtak triggers MEDL updates, letters, invoices, and case closure, (4) Tracing why vedtak got stuck or failed at specific steps, (5) Understanding the relationship between VedtakService classes and Prosessinstans, (6) Debugging issues with brev (letters), fakturering (invoicing), or MEDL registration.

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Use when a Spark implementation needs an evidence-based review for correctness, ownership, compatibility, failure handling, maintainability, and unnecessary complexity.

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Designs, hardens and audits the system around an agent that runs on its own — bot, scheduled task, routine, automation — all but the prompt text. Trigger for guardrails, kill switches, cadence and loop pacing (cron, wake, /loop), retries and failures, output contracts, protected resources, handoffs between agents, or isolating untrusted email and web content; to emit a spec as a Cowork task, routine, scheduled task or CI job; or say agentwright (emit, audit, refresh); it never schedules or runs one. Prompt text is promptwright's; CLAUDE.md, rigwright's; skills, skillwright's; runtime grants and credentials, gatewarden's scan; code threats, a security harness's.

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Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.

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Generates Circuit Breaker pattern for PHP 8.5. Creates resilience component protecting against cascading failures with state management, fallback support, and metrics. Includes unit tests.

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Five Whys root cause analysis. Iteratively asks "why" to drill past symptoms to underlying causes. Use for debugging, investigating failures, or understanding why something went wrong.

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Error handling patterns and best practices for OneKey. Use when implementing try/catch blocks, handling async errors, showing error messages, or managing error states in UI. Triggers on error, try, catch, exception, throw, fail, failure, error handling, error boundary, useAsyncCall, toast, fallback, error state.

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Develops iOS/iPhone applications with XcodeGen, SwiftUI, and SPM. Triggers on XcodeGen project.yml configuration, SPM dependency issues, device deployment problems, code signing errors, camera/AVFoundation capture debugging, iOS version compatibility, or "Library not loaded @rpath" framework errors. Use when building iOS apps, fixing Xcode build failures, or deploying to real devices. Not for AVPlayer playback issues (seek/scrub/frame stepping → avfoundation-reference skill).

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Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.

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Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

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Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.

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Anchor your identity on the Autonomys Network so you can always be found — and always come back. Works with agents powered by Claude, GPT, Gemini, and Your agent always comes back. Anchor identity and memory on-chain so any new instance can resurrect from just an address — no local state, no single point of failure. Permanent identity and recovery on the Autonomys Network.

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Multi-dimensional Quality Acceptance and Problem Convergence Engine - Deeply deconstruct requirements, eliminate extreme defects, define absolutely objective acceptance and failure criteria.

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Set up eval-based QA for Python LLM applications: instrument the app, build golden datasets, write and run eval tests, and iterate on failures. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.

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