diagnose
無料Use when the user reports a hard bug, unexpected failure, or performance regression that needs root-cause analysis.
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。
5,244 件 ・ 関連度順
概要と使いどころ
Use when the user reports a hard bug, unexpected failure, or performance regression that needs root-cause analysis.
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。
Central entry point of the afonsoft agent harness. Use when starting a new project, resuming an existing one, planning features/Epics/releases, or running any multi-step agent-driven work. Validates and reconciles SPECs (SDD), audits the codebase and harness for gaps (security, architecture, performance, hygiene), proposes improvements, fragments work into GitHub Issues, delegates implementation/QA/review to specialized skills, and re-validates everything until delivery. Also use to review unapproved SPECs, reconcile open GitHub Issues with code, or run a final gap check before closing a release.
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 auditing UI code for interface-guideline compliance (accessibility, forms, animation, images, performance, UX copy) and/or validating a deployed page against Lighthouse 95+ targets. Produces evidence-based findings (file:line + Lighthouse JSON) and turns confirmed pendencies into Draft SPECs via write-specs. Do NOT use to design/build UI from scratch (use design) or to fix findings inline — fixes go through the SPEC 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。
Translate motion, interaction, and visual experience into implementable constraints while preserving accessibility and performance. Apply when working on animations, transitions, scroll effects, or micro-UX.
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。
Kova/OpenClaw validation: benchmarks, release gates, scenarios, perf reports.
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 receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
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。
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
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 this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx or .dotx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
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 the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Also use for vague feedback that real footage looks dark, flat, boring, should feel retro/camcorder/print/ASCII, needs privacy, or needs a media reveal.
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。
Run frontend functional, accessibility, visual, and performance test planning with structured reports.
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。
Perform passive reconnaissance and leak intelligence collection with no direct contact to target systems.
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。
GodoMaster — Godot 4.x game development intelligence: GDScript, nodes/scenes, 2D/3D rendering, physics, animation, UI, audio, input, shaders, networking, performance, export, file I/O, testing, localization, AI behavior, asset pipeline, and architecture tooling. Complete workflow for indie and professional game development based on official Godot documentation.
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。
Technical SEO audit with GEO-specific checks — crawlability, indexability, security, performance, SSR, and AI crawler access
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。
GEO-first SEO analysis tool. Optimizes websites for AI-powered search engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) while maintaining traditional SEO foundations. Performs full GEO audits, citability scoring, AI crawler analysis, llms.txt generation, brand mention scanning, platform-specific optimization, schema markup, technical SEO, content quality (E-E-A-T), and client-ready GEO report generation. Use when user says "geo", "seo", "audit", "AI search", "AI visibility", "optimize", "citability", "llms.txt", "schema", "brand mentions", "GEO report", or any URL for analysis.
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。
INTERNAL sub-agent, not a user-facing skill. Performs context-isolated nine-dimension rubric scoring for cheat-score, cheat-predict, and cheat-bump. Accepts only script and rubric-note paths, returns strict JSON, and refuses post-publish evidence.
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。
GStack engineering-manager plan review for architecture, data flow, APIs, migrations, edge cases, tests, performance, release risk, and implementation boundaries.
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。
Research and stress-test open-source project names, from collision checks to launch-ready decisions. Use when the user asks to name or rename a project, compare candidate names, screen GitHub or package namespace risk, verify language or mythology claims, or improve SEO/GEO clarity. Perform live web and registry research, separate brand from category descriptor, classify collisions, and return one evidence-backed recommendation.
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。
Distributed machine learning, data mining, and iterative HPC with Exasol. Covers end-to-end ML pipelines (DISTRIBUTE BY + SET scripts + BucketFS), per-entity federated training with partial_fit and ctx.reset(), batch inference, map-reduce ensemble training, distributed ensemble and SON algorithm for frequent itemset mining (Apriori, FP-Growth, association rules, market-basket analysis), Lua execute script orchestration for iterative algorithms (k-means, SGD, gradient descent), scikit-learn model training, parallel hyperparameter search, per-entity forecasting, anomaly detection, model lifecycle in BucketFS (pickle/joblib/ONNX versioning), GPU acceleration via CUDA SLCs (PyTorch/TensorFlow/RAPIDS), and ML-specific performance tuning (skew, OOM, multi-pass chunking).
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。
Reusable skill for coding agents (Claude, GPT, etc.) to build, optimize, debug, and productionize AI agents and coding agents in Rust. Embeds Rig/ADK patterns, Tokio async architecture, tracing observability, performance techniques, erro...
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 the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
Convex code reviewer — security, auth, validators, performance, and pattern checks for code in a convex/ directory. Use to review or audit Convex functions before shipping.
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。
Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.
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。
Performs a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the user mentions polish, finishing touches, pre-launch review, something looks off, or wants to go from good to great.
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。