5,023 件 ・ 関連度順
概要と使いどころ
Rigorously review code or pull requests for correctness, security, accessibility, maintainability, tests, and edge cases. Use when users request a critical code review, want a guided walkthrough of findings, need implementer-facing feedback, or want to prepare, create, or submit a GitHub pull request 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。
几何识别与图像分割结果地理转换算子。用户提到图像分割分析、遥感分割定位、地理坐标映射时优先调用。
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, debug, or maintain a Hugging Face Space using Gradio, Docker, or Static SDKs. Use for general Space hosting and configuration; use huggingface-zerogpu for ZeroGPU runtime constraints and lora-space-builder for LoRA demos.
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。
Audit and improve project-rules files (AGENTS.md, CLAUDE.md, .agents/instructions, local overrides) so the agent keeps accurate project context. Use when the user asks to check, audit, review, update, improve, or fix their AGENTS.md or CLAUDE.md, mentions "project rules maintenance" or "agent context optimization", or when the codebase has changed enough that the rules file may be stale. Scans the repository for every rules file, grades each against a quality rubric, outputs a quality report, and applies targeted edits only after user approval.
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。
Agents should invoke this skill for code reviews, linting/formatting setup, maintainability checks, complexity concerns, warning cleanup, coding standards, or quality gates in Rust, TypeScript, Python, shell, and mixed repos.
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。
Analyzes recent CI failures on pull requests to identify flaky tests, using retry outcomes (failed attempt → green re-run) and cross-PR recurrence as evidence, and maintains a local longitudinal ledger so flakiness can be tracked over time. TRIGGER when: the user wants to find flaky tests, correlate recent CI failures, check which tests fail across PRs or recover on retry, or refresh the flakiness trend report. DO NOT TRIGGER when: babysitting a single PR's CI until green → monitoring-pull-requests; diagnosing or fixing one specific failing test → the bug-analysis 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。
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
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。
TDD workflow for migrations - orchestrate agents, zero main context growth
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。
Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.
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。
Hierarchical memory organization for multi-session context retention. Wings (projects) > Rooms (domains) > Drawers (decisions). Semantic search across all memories with zero cloud dependency.
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 patterns, best practices, and conventions for building robust, efficient, and maintainable Go applications.
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。
Email delivery infrastructure - DNS authentication (SPF/DKIM/DMARC), subdomain isolation, provider abstraction, template systems, bounce handling, warmup strategy, and deliverability monitoring.
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。
LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming patterns.
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。
Implement and maintain compliance with SOC 2, HIPAA, PCI-DSS, and GDPR using unified control mapping, policy-as-code enforcement, and automated evidence collection. Use when building systems requiring regulatory compliance, implementing security controls across multiple frameworks, or automating audit preparation.
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 APIs that are secure, scalable, and maintainable using RESTful, GraphQL, and event-driven patterns. Use when designing new APIs, evolving existing APIs, or establishing API standards for teams.
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。
Manage DNS records, TTL strategies, and DNS-as-code automation for infrastructure. Use when configuring domain resolution, automating DNS from Kubernetes with external-dns, setting up DNS-based load balancing, or troubleshooting propagation issues across cloud providers (Route53, Cloud DNS, Azure DNS, Cloudflare).
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。
Check current Claude usage limits (session and weekly) with ASCII progress bars. Trigger when the user asks about usage, quota, limits, rate limits, how much Claude they've used, remaining capacity, or phrases like "check usage", "usage status", "how much quota left", "am I close to the limit", "用量", "额度", "配额".
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。
Generate Nano Banana Pro (Gemini 3 Pro Image) prompts for e-commerce product photography. Given a user-uploaded product photo, this skill identifies the main subject, asks the user to choose a scene type, then outputs a professional, ready-to-paste English prompt optimized for Nano Banana Pro's image-to-image capabilities. Use this skill whenever the user uploads a product image and wants to generate an e-commerce photo, product shot, commercial image, or marketing visual using Nano Banana Pro / Gemini. Trigger phrases include: "ecom shot", "电商图", "产品图", "商品图", "product photo", "e-commerce image", "make a product shot", "generate a Nano Banana prompt for this product", "帮我做一张电商主图", "白底图", "商拍", "产品摄影", "hero shot", "packshot", or any request involving turning a casual product photo into a professional commercial image. Also trigger when the user mentions Nano Banana / Gemini image generation with a product photo.
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。
Execute exactly one eligible Unit in an existing research Workspace; use for stepwise or manual semantic execution when status, Attempt, Artifact, Manifest, checkpoint, and acceptance evidence must remain synchronized.
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。
Compile a LaTeX project and run basic QA (missing refs, bib errors, broken citations), producing `latex/main.pdf` and a build report.
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。
Scaffold a LaTeX project (`latex/main.tex`, optional bibliography wiring, structure) from an existing Markdown draft.
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。
Maintain bounded, durable AI project memory in a repository's docs/ai/ pack. Use when Codex or Claude Code needs to create, read, update, or audit project memory (project-card, architecture, diagrams, runbook, handoff, gotchas, ADRs), install AGENTS.md memory rules, or sync a lightweight central LLM Wiki project entity for user-owned projects.
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。
Query and maintain the user's local LLM Wiki from any Codex or Claude Code conversation or project. Use when the user asks to search personal knowledge, recall prior research or decisions, answer from the wiki, create durable notes, ingest a source into the wiki, update topic/concept/entity/question pages, write back useful answers, or run wiki lint/reindex workflows.
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。
Summon shadow clones: genjutsu's full-scale pipeline for a whole website or web app, from scratch or as a full redesign. Harvests the client's real material, researches in parallel, lets Impeccable lead the direction and genjutsu the motion, builds the pages with parallel agents, then loops fixes, verdicts and a cold-eyes art director until only minor issues remain, the round cap of the chosen tier is reached, or a round fixes nothing. Announces its cost first and asks twice. Web. Needs a host that can spawn subagents.
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。