2,543 件 ・ 関連度順
概要と使いどころ
Expert Bash help for writing, debugging, and optimizing safe, portable shell one-liners and scripts on macOS/Linux. Use when users ask for Bash or POSIX sh commands, script reviews, ShellCheck fixes, quoting/pipeline issues, process/file automation, or converting requirements into shell scripts.
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。
UI 資產品質驗證 SKILL — 執行 validate-visual-assets.js、validate-ui-specs.js 與必要的 snapshot regression，對 skin family 資產、screen package、proof draft / family-map 進行全面驗證，並回寫 generated-review。USE FOR: 任何 UI 資產生成後、在 ui-preview-judge 前必須先通過的 QA 關卡。DO NOT USE FOR: debug runtime 崩潰（用 cocos-log-reader）、Layout 佈局調整（用 ui-vibe-pipeline）。
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。
COMPLETE BUG INVESTIGATION WORKFLOW — Combines screenshot + log reading into a full triage pipeline. USE FOR: any bug report that has both visual symptoms AND runtime errors, especially CompositePanel / ChildPanel mount failures, screen spec wiring breaks, or battle scene UI crashes. This is the master debugging workflow that orchestrates cocos-screenshot and cocos-log-reader together.
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。
BROWSER VFX ACCEPTANCE SKILL — Use built-in browser/headless browser to automatically verify Cocos VFX block effects and composed VFX recipes in BattleScene preview (`http://localhost:7456`, `previewMode=true`, `previewTarget=5`). USE FOR: VFX health audit, per-block smoke validation, combo recipe regression checks before merging `vfx-block-registry.ts` / `vfx-effects.json`. DO NOT USE FOR: Cocos Editor window screenshot capture, compile-error debugging, or pure log-only diagnosis without browser preview.
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。
Idiomatic Go - package and interface design, error wrapping, table-driven tests, generics, the modern standard library (slices/maps/cmp/errors.Join), current syntax, and logging discipline. Use when writing, reviewing, or refactoring any Go code, especially code drifting toward Java/Spring shapes (deep layer trees, generic repositories, heavy frameworks) - even if the user never says "idiomatic". Distilled from spf13/go-skills and adapted to this repo.
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。
Review a Go design spec before implementation begins - dispatch a subagent that checks a design doc for completeness, consistency, and idiomatic Go (simplicity, small consumer-defined interfaces, explicit wrapped errors, context propagation) plus Cobra/Viper conventions where applicable. Use when a user has a Go spec to review, asks "is this spec ready?", or is about to implement from a written design. Distilled from spf13/go-skills and adapted to this repo's conventions.
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。
Idiomatic Go concurrency - sync primitives, channel semantics, the select statement, and the standard channel patterns (cancellation/done-channel, fan-out/fan-in, pipeline, or-done, context, worker-pool). Use when writing or reviewing Go that spawns goroutines, shares state, or coordinates over channels, even if the user never says "concurrency" - e.g. data races, deadlocks, goroutine leaks, sync/context/select usage, or "make this parallel". Distilled from luk4z7/go-concurrency-guide.
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。
Modify NPC behavior, HTN tasks, navigation, steering, prototypes, and AI debugging.
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。
Reproduce failures, trace authoritative flow, prove the broken assumption, and add targeted regression coverage.
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。
Capture durable project memory from work, debates, debugging discoveries, learned conventions, deferred options, and session outcomes. Load when the user says remember this, save this learning, record what happened, update project memory, or preserve context for future agents.
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。
Capture actionable learnings that emerge during conversation — when the agent or user discovers that a skill, a set of skills, or a process needs to be updated based on what's happening in the current chat. Sub-skill of the learn-from orchestrator. Load when the user says "we should update the skill for this", "this should be a skill rule", "add this as a gotcha", "the skill should know about this", "update the process for this", "remember this for next time", "this is important for the skill". Also triggers when the agent notices a skill's guidance was wrong or incomplete, a process step failed or was unnecessary, a new pattern emerged, a guardrail was missing, a workaround became a pattern, or a debugging session reveals a gap.
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。
Append structured execution traces across operational, cognitive, and contextual surfaces with minimal overhead. Load when inspecting agent runs, logging tool calls and observations, enabling post-run debugging, or pairing with structured-planning step IDs. Also triggers on "trace this run", "log execution", "agent observability", "run log", or when fault-localize needs evidence. Default-on during multi-step plans. Traces live at .agent-loom/traces/ — git-ignored by default.
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。
Instrument a shipped product's AI agents with tracing and observability so you can see what they did, why outputs happened, and what each run cost. Plain-language primer plus free-tier-first backend selection (Langfuse, Phoenix, LangSmith, Braintrust) and OpenTelemetry/OpenInference instrumentation. Load when the user asks to add observability, add tracing, instrument my agents, see what my agent is doing in production, set up Langfuse or Phoenix or LangSmith, debug why my agent gave a bad answer, or track LLM cost per request. Also fires when agent-system-architecture or setup-evaluation requires an observability plan for an agent-chain product. NOT for tracing the coding agent itself — that is run-trace. Precondition for runtime-learning-loop.
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。
Prisma ORM CLI commands reference covering init, generate, migrate, db, dev, complete, studio, validate, format, debug, and mcp. Use for ORM/database CLI workflows, not the Prisma Platform CLI. Triggers on "prisma init", "prisma generate", "prisma migrate", "prisma db", "prisma complete", "prisma studio", "prisma mcp".
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。
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
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 debug spreadsheet formulas (Excel/Google Sheets), pivot tables, and array formulas; translate between dialects; use when users need working formulas with examples and edge-case checks.
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。
Inspect GitHub PR checks with gh, pull failing GitHub Actions logs, summarize failure context, then create a fix plan and implement after user approval. Use when a user asks to debug or fix failing PR CI/CD checks on GitHub Actions and wants a plan + code changes; for external checks (e.g., Buildkite), only report the details URL and mark them out of scope.
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 browser automation expert who has debugged thousands of flaky tests and built scrapers that run for years without breaking. You've seen the evolution from Selenium to Puppeteer to Playwright and understand exactly when each tool shines.
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 finds and fixes bugs using proven debugging techniques. Traces from symptoms to root cause, implements fixes, and prevents regression.
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。
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
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 an AI product engineer who has shipped LLM features to millions of users. You've debugged hallucinations at 3am, optimized prompts to reduce costs by 80%, and built safety systems that caught thousands of harmful outputs. You know that demos are easy and production is hard.
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。
Handles BED-format genomic intervals (BED3 through BED12, narrowPeak/broadPeak) and the coordinate-system substrate the whole interval category rests on, with bedtools (CLI) and pybedtools/pyranges/pandas (Python). Covers the 0-based half-open vs 1-based-closed convention boundary and the start-1/end-unchanged conversion, the silent failures (chrom-name mismatch, CRLF, lexicographic-vs-version sort under -sorted), genome/chrom.sizes generation, sorting contracts, BED12 block invariants, validation, makewindows, cross-assembly liftover (liftOver/CrossMap), and BED<->VCF/BAM/FASTA conversion. Use when reading, creating, validating, sorting, lifting between genome builds, or converting interval files, preparing inputs for bedtools/tabix/bigBed, or debugging an off-by-one or empty-overlap result.
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。
Loads, converts, and manipulates Hi-C contact matrices in cooler format (.cool/.mcool/.scool) and Juicer .hic, using cooler (Python + CLI), hic2cool, and hictk. Covers the single-resolution mcool URI (file.mcool::/resolutions/<bp>), the load-bearing divisive-vs-multiplicative weight-naming rule (KR/VC/VC_SQRT auto-divisive vs cooler's multiplicative weight), what survives .hic<->.cool conversion (FRAG matrices and norm vectors do not), raw-vs-balanced coarsening, the .pairs upper-triangle/chromsize-order contract, and chrom-naming/bin-table provenance. Use when loading a cooler, converting .hic to .mcool, selecting a resolution, building a cooler from pairs or a matrix, coarsening/zoomifying, importing Juicer norm vectors, or debugging all-NaN balanced matrices and chr1-vs-1 empty fetches.
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。
Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.
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。