1.6천건 · 관련도순
Fix failing ToolUniverse tools by diagnosing test failures, identifying root causes, implementing fixes, and validating solutions. Use when ToolUniverse tools fail tests, return errors, have schema validation issues, or when asked to debug or fix tools in the ToolUniverse framework.
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Investigate errors, incidents, or product ideas using both internet research and repo-wide codebase research, then propose a concrete changeset plan with clarifying questions before any implementation. Use when a user asks to investigate, root-cause, or plan changes, or when an Issue or PR is referenced and needs a plan.
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Diagnoses and fixes CI failures and re-runs GitHub Actions jobs. Use when CI is failing, tests break in CI, lint errors block merging, a build fails, or jobs need re-running.
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React Hook Form v7 (RHF、非制御フォームライブラリ) リファレンス。別名 rhf / React-Hook-Form。 useForm, register, handleSubmit, watch, setValue, getValues, getErrors, reset、 Controller, useFieldArray / FieldArray, formState / FormState, ErrorMessage、 resolver (Zod / Yup / Joi)、バリデーション、Server Actions / useActionState、 DevTools (@hookform/devtools)、TypeScript 型。
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Claude API (platform.claude.com) の Messages API リファレンス。 streaming (SSE), thinking (adaptive) / preserved thinking / effort, prompt caching, context editing, compaction (on-demand / threshold), structured outputs, Message Batches, token counting, vision / PDF, Files API, citations, embeddings (Voyage AI), errors, rate limits, beta headers, Bedrock / Vertex AI / Foundry 経由アクセス。
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Compile the Unity project and report errors/warnings. Use after C# edits or when a full Domain Reload compile is needed.
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Read current Unity Console entries from a running Editor. Use during bug investigation after compile, tests, PlayMode, or dynamic code to inspect logs, warnings, errors, and stack traces.
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Predicts protein-coding gene structures (exons, introns, UTRs) in eukaryotic genomes with BRAKER3 (RNA-seq + protein evidence), BRAKER1/BRAKER2, GALBA (protein-only), Funannotate (fungi), GeMoMa (homology projection), or Helixer/Tiberius (deep-learning ab initio). Covers the evidence-first tool decision, mandatory soft-masking, the training-set-quality-dominates principle, OrthoDB clade-partition selection, the one-isoform-per-locus and missing-UTR traps, merge/split errors, and reference bias against orphan genes. Use when annotating a newly assembled eukaryotic genome, choosing a gene-prediction pipeline based on available evidence, or diagnosing a poor annotation.
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Assembles haplotype-resolved diploid and telomere-to-telomere (T2T) genomes from PacBio HiFi reads with hifiasm (HiFi-only, Hi-C, or trio phasing) and verkko (HiFi + ultralong ONT for T2T), extracting contigs from GFA and routing phasing QC to k-mer/trio metrics. Covers why a primary assembly is a haplotype mosaic that exists in no cell, partial-vs-full phasing (the .bp. vs .dip. filename convention), the purge-default trap on inbred samples, the --hom-cov coverage-estimate alarm, and verkko-vs-hifiasm for T2T. Use when assembling a diploid eukaryote from HiFi, phasing haplotypes with parents (trio) or Hi-C, deciding whether to chase T2T, or diagnosing switch errors invisible to N50/BUSCO/QV.
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Evaluates genome assembly quality across the three orthogonal axes - contiguity (QUAST auN/NG50/NGx, not bare N50), completeness (BUSCO/compleasm gene-space plus Merqury k-mer completeness), and correctness (reference-free Merqury QV, Inspector/CRAQ structural errors, asmgene false-duplication/collapse). Covers why N50 is the most-gamed metric, why QV measured on the polishing reads is circular, distinguishing uncollapsed haplotigs from real WGD, and the EBP/VGP 6.C.Q40 standard. Use when judging whether an assembly is good enough to annotate or publish, comparing assemblers, diagnosing a fragmented or duplicated assembly, or assessing a phased diploid assembly.
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Run convex-doctor static analysis, interpret findings, and fix issues across security, performance, correctness, schema, and architecture categories. Use when running convex-doctor, fixing convex-doctor warnings or errors, improving the convex-doctor score, or when asked about Convex code quality, static analysis, or linting Convex functions.
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Find root cause of errors, crashes, regressions, failing tests before any fix. Not for code review or new features.
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Convert AmeriFlux ERA5 half-hourly meteorological CSV files into EcoSIM hourly climate forcing NetCDF files, compare generated forcing against overlapping measured tower meteorology when a FULLSET file is available, and report large biases or errors. Use when preparing or validating EcoSIM climate inputs for AmeriFlux sites, checking ERA5 against in situ records, diagnosing forcing discrepancies, or writing climate-quality reports. For non-AmeriFlux paper sites that need a fresh Copernicus CDS ERA5 point download by longitude/latitude, use era5-cds-point-download first.
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Design traceable API checks for contracts, authentication, authorization, errors, and idempotency with observable outcomes.
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Super-skill for developing Haskell projects with cabal nix-style builds. Orchestrates HLS diagnostics, Haddock, Hoogle, source formatting, and cabal-gild into one workflow. Use when writing, editing, refactoring, building, typechecking, fixing compiler errors, renaming symbols, looking up APIs, or changing dependencies in Haskell projects. Treat cabal.project as the source of truth, prefer HLS before full builds, and prefer local docs over remote lookup.
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Write type-safe TypeScript code with strict mode enabled, comprehensive type definitions, proper error handling, and elimination of any types. Use when enabling TypeScript strict mode, adding types to existing JavaScript, fixing type errors, creating type definitions, using utility types, implementing type guards, avoiding any types, creating generic types, or ensuring complete type safety across the codebase.
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Implement comprehensive monitoring, logging, metrics, tracing, and alerting for production applications to ensure reliability and quick incident response. Use when setting up application monitoring, implementing structured logging, creating metrics and dashboards, setting up alerts, implementing distributed tracing, monitoring performance, tracking errors, or building observability into applications.
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Trace bugs backward through call stacks and execution flows to identify the original source of errors, invalid data, or incorrect behavior. Use when debugging complex issues, tracing error origins, investigating data corruption, following execution paths, identifying where invalid data enters the system, or finding root causes of cascading failures.
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When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," or "indexing issues." Use this even if the user just says something vague like "my SEO is bad" or "help with SEO" — start with an audit. For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup. For AI search optimization, see ai-seo.
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Use when asked to debug, fix a bug, investigate an error, or do root cause analysis, and when users report errors, stack traces, unexpected behavior, or say something stopped working.
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Post-deploy canary monitoring. Watches the live app for console errors, performance regressions, and page failures using the browse daemon. Takes periodic screenshots, compares against pre-deploy baselines, and alerts on anomalies. Use when: "monitor deploy", "canary", "post-deploy check", "watch production", "verify deploy". (gstack)
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Triage AEM Workflow issues on AEM as a Cloud Service by classifying symptoms, gathering the right logs and metrics, and mapping to runbooks or Splunk searches. Use when the user asks for workflow activity/errors on a Cloud Service host, needs to classify a Jira ticket, or wants to know what to collect for workflow debugging.
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Debug AEM Workflow issues on AEM as a Cloud Service — stuck workflows, failed steps, missing Inbox tasks, launcher failures, stale instances, thread pool exhaustion, queue backlogs, purge failures, and permissions errors. Use when the user reports workflow problems on Cloud Service, asks why a workflow is stuck or failed, needs step-by-step troubleshooting, or provides thread dumps, configuration status output, or Sling Job console output for analysis.
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Implement custom AEM Workflow Java components on AEM as a Cloud Service. Use when writing WorkflowProcess steps, ParticipantStepChooser implementations, registering services via OSGi DS R6 annotations, reading step arguments from MetaDataMap, accessing JCR payload via WorkflowSession adapter, reading and writing workflow metadata and variables, and handling errors with WorkflowException for retry behavior.
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