7,616 件 ・ 関連度順
概要と使いどころ
Continuous self-improvement system for Hermes Agent. Analyzes your past sessions to find recurring failures and skill gaps, then automatically creates or patches skills and runs self-evolution to fix them. Set it to run overnight and wake up to a better agent. Use /dojo to start.
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。
This skill should be used when the user asks about "bun build", "Bun.build", "bundling with Bun", "code splitting", "tree shaking", "minification", "sourcemaps", "bundle optimization", "esbuild alternative", "building for production", "bundling TypeScript", "bundling for browser", "bundling for Node", or JavaScript/TypeScript bundling with Bun.
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。
Post-event analyst note (conferences, KOL events, site visits) with the professional note anatomy — headline verdict, per-stock takeaways with model numbers, KOL distillation, cross-trial comparison lattices, modeled deltas vs consensus (peak × POS), three what's-changed vectors, risk bullets, and materiality-rated conflicting views. Use after any med event to convert the event into actionable takeaways.
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。
Produce video with Moonvalley's Marey model family (Marey Realism v1.5) — a filmmaker-oriented, 1080p/24fps generative video model marketed as trained exclusively on licensed data. Use this skill when a task asks for Marey or Moonvalley specifically, when a brief demands brand-safe / legally reviewed AI video for commercial or studio work, or when the request needs Marey's director-style controls (camera trajectory, motion transfer, pose transfer, keyframing, reference conditioning). It covers what "commercially safe" really means versus the actual terms of service, access routes (Moonvalley web / Voyager, the fal API, ComfyUI), pricing, capability limits, prompt and reference strategy, where Marey fits production versus where other models win, iteration, and quality review. Do not use it for audio generation, for photoreal talking-head dialogue, or as a generic "best video model" 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。
Captions living in 3D space around a talking head: a camera flies between the speaker and the words (whip-in, parallax truck, push), caption groups sit at different depths so camera moves pull them apart, hero words hide BEHIND the speaker through an alpha matte, a ring of words wraps round the speaker and turns in front of them, focus racks between depths, and text steps at 15 fps with ghost motion blur. Works in any type style (editorial serif, bold sans) or hand-drawn (p5.brush write-on). Trigger on: "3D text", "3D camera captions", "text around / behind the speaker", "camera moves through the text", "depth captions on my avatar video". Covers prep (portion, padded plate, matte, word clock, font metrics), the shot grammar, depth rules, QC, and limits.
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。
Call protein-RNA binding sites from CLIP-seq BAM with CLIPper, PureCLIP, Skipper, Piranha, omniCLIP, CTK, CLAM, or Paraclu. Use when choosing between coverage-based, HMM-based, beta-binomial window-based, and crosslink-site-based peak callers; applying ENCODE eCLIP thresholds (log2 IP/SMInput >= 3, -log10 p >= 3); deciding when SMInput is mandatory; or reconciling peak-set discordance between callers for the same RBP.
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。
End-to-end ChIP-seq workflow from FASTQ files to annotated peaks. Covers QC, alignment, peak calling with MACS3 (or HOMER), and peak annotation with ChIPseeker. Use when processing ChIP-seq data from alignment through peak annotation.
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。
Implements Manus-style file-based planning to organize and track progress on complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when asked to plan out, break down, or organize a multi-step project, research task, or any work requiring >5 tool calls. Supports automatic session recovery after /clear.
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 automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
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 the konsistent CLI, review all reported violations, and fix them in the codebase. Use when the user wants to "fix konsistent violations", "resolve konsistent errors", "clean up konsistent diagnostics", "make konsistent pass", "address structural convention violations", or asks to run konsistent and act on the results. The skill is interactive: it requires explicit user decisions when many violations stem from the same rule (rule vs. code question), explicit user confirmation before modifying any code, and a triage step for non-trivial violations. For editing `konsistent.json`, this skill defers to the `konsistent-config` skill.
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 a whole regression suite and prune/restructure it with evidence: per-test coverage fingerprinting, AST near-duplicate clustering, CI-history mining for never-failing and flaky tests, prune decision rules (redundant/obsolete/low-value/keep), smoke/core/extended tiering by risk and defect-detection history, and a defensible "what we deleted and why" record. Deletion is destructive — quarantine and human sign-off are mandatory. Use when: "audit the test suite," "prune redundant tests," "find duplicate tests," "which tests can we delete," "restructure into smoke/core/extended," "is this test pulling its weight," "shrink the regression suite." Not for: Judging whether an individual test is WELL-WRITTEN (smells, assertions) — that is ai-qa-review. Healing one flaky test at runtime — that is test-reliability. Bulk selector regeneration after a UI refactor — that is selector-drift-recovery. Related: ai-qa-review, coverage-analysis, test-reliability, risk-based-testing, qa-project-context.
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。
Remove AI-generated patterns from QA reports, bug reports, test summaries, status updates, and quality communications. Detects and rewrites robotic test-result language, template-sounding status updates, inflated severity descriptions, and generic stakeholder reports — without inventing facts. Makes QA writing sound like a real engineer wrote it. Use when: "humanize report," "rewrite QA summary," "fix test report," "make this sound human," "clean up status update." Not for: general prose, blog, or marketing-copy cleanup — use the global humanizer skill. Not for: classifying or routing CI failures — use ai-bug-triage. Related: ai-bug-triage, qa-metrics, qa-dashboard, quality-postmortem.
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。
Runtime per-test healing with evidence: multi-attribute selector healing, environment-aware diagnosis, flake classification, quarantine management, and confidence-scored auto-repair. Goes beyond simple locator fallbacks to cover action-level healing, data healing, and observable repair workflows. Use when: "flaky test," "test stability," "self-healing locator," "broken locator recovery," "unreliable test," "quarantine flaky test." Not for: bulk regenerating selectors after a planned UI refactor — use selector-drift-recovery (this skill heals ONE test at runtime; that one rewrites many tests offline). Not for: classifying/clustering CI failures into bug reports — use ai-bug-triage. Related: playwright-automation, selector-drift-recovery, ci-cd-integration, qa-metrics, ai-bug-triage.
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。
Symfony UX frontend stack -- decision tree and orchestrator for choosing between Stimulus, Turbo, TwigComponent, LiveComponent, UX Icons, and UX Map. Use when the user is unsure which tool fits, wants to combine multiple UX packages, or asks a general frontend architecture question in Symfony. Also trigger when the user asks "which UX package should I use", "how to make this interactive", "should I use Stimulus or LiveComponent", "how to structure my Symfony frontend", "what is the difference between Turbo and LiveComponent", "should this be a Frame or a LiveComponent", "how do these UX packages work together", "what is the Symfony way to do frontend". Do NOT trigger when the user clearly names a specific tool (stimulus, turbo, twig-component, live-component, ux-icons, ux-map) -- defer to the specialized skill instead.
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 read, create, or edit Korean Hangul Word Processor documents (.hwp or .hwpx files). Triggers include any mention of 'hwp', 'hwpx', '한글 문서', '아래한글', '한컴오피스', or uploading/attaching .hwp/.hwpx files. Also use when extracting text from Korean reports or producing Korean-formatted official documents (공문, 보고서, 계약서, 사업계획서). Do NOT use for Word .docx files (use the docx skill instead) or general Korean text without Hangul Word Processor format. ⚠️ SECURITY: if the task fills a form with personal data (주민등록번호·계좌·연락처·주소 등), LOAD THIS SKILL FIRST — before any `ls`/`cat`/`Read`/`grep` of the working dir or home — and NEVER directly cat/Read/grep a profile or 내정보 file (e.g. ~/.claw-hwp/profile.txt), even "to check it". Its SECURE FILL flow reads values in-process only; reading them yourself leaks them into context.
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。
Продающие страницы и представительские тексты на русском языке: лендинги, промостраницы, страницы продукта, услуги, тексты о себе, профили, отклики, страницы компании, миссии и пресс-релизы. Use this skill whenever the user asks to write, audit, structure, or improve a Russian landing page, promo page, sales page, product page, service page, about-me text, job application, company page, mission, press release, homepage copy, or text describing services. Триггеры: «лендинг», «промостраница», «продающий текст», «страница продукта», «текст о себе», «отклик на вакансию», «о компании», «миссия», «пресс-релиз», «опиши мои услуги», «текст для главной». Для коротких постов см. skill post; для статей и лонгридов — statya; для текстов интерфейса — ux-copy.
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。
Короткие русскоязычные посты для Telegram, LinkedIn, Instagram и других соцсетей: пост с нуля, пост из статьи, анонс в канал, переписывание первой строки, усиление хука и финала. Use this skill whenever the user asks to write, rewrite, draft, shorten, or improve a Russian social media post, Telegram channel post, LinkedIn post, Instagram caption, channel announcement, post from an article, or first-line hook. Триггеры: «пост в телеграм», «пост для канала», «пост в LinkedIn», «пост в Instagram», «короткий пост», «напиши пост», «анонс в канал», «пост из статьи», «первая строка не цепляет», «перепиши пост». Для статей и лонгридов см. skill statya; для лендингов и продающих страниц — promo; для интерфейса — ux-copy.
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。
dlt (data load tool) is an open-source Python library that loads data from APIs, files and databases into warehouses and lakes, inferring the schema and tracking incremental state for you. Use when a user asks to build a data pipeline in Python, load a REST API into DuckDB, BigQuery, Snowflake or Postgres, set up incremental or merge loading, enforce a schema contract, or replace a hand-written ETL script or a hosted ELT connector.
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 project dependencies for outdated packages, security vulnerabilities, and breaking changes. Use when someone asks to "check for outdated packages", "audit dependencies", "find vulnerable dependencies", "plan dependency upgrades", "detect breaking changes", or "update npm packages safely". Analyzes package.json/lock files, cross-references changelogs, and produces ordered upgrade plans.
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 Wi-Fi networks with the aircrack-ng suite. Use when a user asks to test their own wireless network, capture WPA2 handshakes, crack captured handshakes offline, put an adapter into monitor mode, or perform a wireless pentest under an authorized engagement.
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。
Expert knowledge for real-time and baked lighting in games - from cinematography fundamentals to engine-specific optimization, covering GI, time-of-day, volumetrics, and platform-aware lighting pipelinesUse when "lighting, light design, baked lighting, realtime lighting, lightmap, lightmapping, light probe, reflection probe, global illumination, GI, ambient occlusion, shadow, shadow cascade, time of day, day night cycle, volumetric fog, volumetric lighting, god rays, HDR, tonemapping, bloom, exposure, emissive, area light, Lumen, Enlighten, ray tracing, RTGI, light baking, lighting, global-illumination, lightmapping, shadows, GI, light-probes, reflection-probes, HDR, tonemapping, volumetric, fog, time-of-day, baked, realtime, mixed-lighting, lumen, enlighten, radiosity, ray-tracing, RTGI" mentioned.
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。
Founders face unique challenges in how they work. Maker vs manager schedule conflicts. Default alive vs dead math. Time and money slowly leaking away. Effective founders develop systems for navigating these challenges. This skill synthesizes PG's essays on founder productivity and decision-making into an operating system for founder effectiveness. Use when "keywords, contexts, " mentioned.
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。
Expert in decision-making frameworks - systematic approaches to making better decisions under uncertainty. Covers decision criteria, reversibility assessment, stakeholder alignment, and decision documentation. Knows when to decide fast and when to deliberate. Use when "decision framework, how to decide, making a choice, tradeoff, should we, pros and cons, decision matrix, weighing options, " mentioned.
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。
Mastery of AI image generation across the full spectrum: Midjourney for aesthetic perfection, Flux for prompt adherence, DALL-E 3 for concept clarity, Stable Diffusion for control, and Imagen 3 for photorealism. This skill transforms text into visual reality at the speed of thought. We've moved beyond "AI can make pictures" to "AI is the fastest concept artist, product photographer, and visual designer ever created." The skill isn't just prompting—it's understanding how each model thinks, what makes images work, and how to systematically produce exactly what you envision. The best AI image generators have internalized composition, lighting, color theory, and style—not by studying art, but by generating thousands of images and learning what works. They're visual directors who happen to work in text. Use when "AI image, generate image, Midjourney, DALL-E, Flux, Stable Diffusion, Imagen, text to image, AI art, AI photo, AI illustration, AI visual, AI graphics, generate picture, ai-image, midjourney, dall-e, flux, stable-diffusion, imagen, generation, text-to-image, visual, art" mentioned.
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。