478 件 ・ 関連度順
概要と使いどころ
Optional Moonbase license-activation integration for Pulp — load-bearing compile settings, OpenSSL-at-configure caveat, the moonbase-pulp User-Agent contract, audio-thread gating + click-free fade, async start/pump, the interactive native (no-WebView) activation editor (frame-tick polling + the don't-rebuild-mid-event trap), loadable plugin/standalone formats, and headless screenshots.
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 and debug "only happens in a DAW" audio plugin bugs (cutouts, glitches, parameter-change failures) entirely offline — headless Processor scenes for DSP bugs and a standalone AudioUnit host probe for adapter/host-interaction bugs. Use when a plugin misbehaves in Logic/Live/etc. but unit tests are green.
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。
Convert Markdown (.md) files to a polished PDF with ALL images preserved and scaled to the page. Use whenever the user asks to "save this markdown as a PDF", "convert README.md to pdf", "export the .md as a pdf", "turn these notes/docs into a PDF", or wants a PDF deliverable of any GitHub-flavored Markdown document (README, design doc, report, notes) — especially when it contains images or diagrams (remote or local), tables, code blocks, or a linked table of contents. Pipeline: pandoc (GFM → standalone HTML with embedded resources) → headless Chrome print-to-pdf with a GitHub-like print stylesheet → pypdf verification that every referenced image is embedded. Do NOT use for .tex → PDF (use a LaTeX toolchain) or for .docx work (use word-docx / tex2docx).
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。
Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping old ones, avoid lazy under-generation, avoid cards-inside-cards-inside-cards UI, and keep the hero clean, spacious, readable, and visible on a small laptop.
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。
Standalone E-E-A-T scoring rubric for a URL or content draft. Scores Experience, Expertise, Authoritativeness, and Trust 0-5 each using concrete detectable signals, framed per Google's creating-helpful-content doc. Use when user says "E-E-A-T", "EEAT", "experience expertise", "trust signals", or "author authority".
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。
Deploy a local project directory or Git repository to Volcengine as a running, reachable cloud service. USE WHEN: deploy to Volcengine, deploy to 火山引擎/火山, deploy this repo/project, publish current code, launch the app, run it in the cloud, expose it as a service, deploy to ECS/VKE/veFaaS, run on ECS, push to VKE, deploy as serverless/FaaS, or the user wants the agent to choose a Volcengine hosting target. If the user only asks which Volcengine deployment target to choose, use `volcengine-prepare` skill first. Not for creating a single standalone resource — use `volcengine-cli` skill for that.
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 any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
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。
Iteratively study and apply elegant coding patterns. Each iteration - understand the code, research what simple and elegant code looks like, apply learnings, verify with CI. Use as a standalone refactoring pass or when the user asks to make code more elegant, simple, or idiomatic.
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 codebase against well-known software design principles: SOLID, DRY, YAGNI, KISS, Law of Demeter, Separation of Concerns, Composition over Inheritance, and the code-relevant 12-Factor subset. Scores findings by impact and effort, runs adversarial debate on contested violations, and generates a prioritized DESIGN_AUDIT.md. Use when reviewing code quality beyond what linters catch, assessing design health before a refactor, or onboarding to an unfamiliar codebase. Can be invoked standalone or delegated from tech-debt.
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。
Analyze existing KiCad projects, schematics, PCB layouts, Gerbers, netlists, and PDF reference schematics. Use when files such as .kicad_sch, .kicad_pcb, .kicad_pro, or Gerbers are supplied and the user wants review, debugging, net tracing, ERC/DRC/DFM, schematic-to-PCB comparison, or pre-fabrication checks. Do not use to create a new design from requirements or for standalone sourcing and ordering.
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。
Create, import, analyze, resume, or revise an end-to-end Circuit Weaver electronic design from requirements through validated functional KiCad schematics, placement review, and a truthful manufacturing handoff. Use for new designs and for existing KiCad/PCB/Gerber projects that need durable state. Use kicad for one-off file inspection, bom for standalone sourcing, and design-wizard only when the user explicitly requests the slower questionnaire.
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 Angular: standalone components, signals, RxJS patterns, DI, and enterprise structure. Use when writing, reviewing, or structuring Angular 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。
Create, write, or manage Meta ads and assets: ad copy, campaigns, spend, reports, audiences, catalogs, product feeds, feed refresh schedules, experiments, and policy. Always load for any request to create or write an ad, or to advertise a product or service, even when no platform is named; this includes sensitive or restricted categories. Always load for any question asking what a Meta, Facebook, or Instagram advertising policy means, allows, prohibits, or requires, including a standalone policy-definition question with no account context. Those questions must use ads_policy_tool, never browser search or memory. Load for a specifically named catalog or feed with an upload or refresh-schedule request; use Ads reads to resolve ownership before writing. Generic unnamed feeds need context. Whether an image, claim or piece of copy may be used in an ad is ALWAYS a Meta Ads task — 'can I use this in an ad', 'is it allowed', 'is this against policy', and any rights, likeness, celebrity, logo or trademark question about advertising with an image, including a follow-up about one just generated. Those are ads-policy questions, not general legal ones. An ad request uses the campaign workflow unless explicitly only an image or organic post.
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。
Create and maintain the shared knowledge/ context files that every other marketing skill reads - brand voice, ICP personas, positioning, KPIs, and the learnings log. Run this once per company or client before using any other marketing skill. Use when the user says "set up brand context", "onboard my brand", "set up the marketing knowledge base", "the skills don't know my brand", "update our positioning", "our voice has changed", "add a new persona", or when any marketing skill reports that a knowledge/ file is missing. Also use when output sounds generic or off-brand. For writing a positioning statement as a standalone document, see positioning-doc. For deep persona research from raw sources, see customer-research.
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 Google NotebookLM notebooks for source-grounded, citation-backed answers from user-uploaded documents. Manages notebook library, handles Google authentication, and supports smart discovery. Works standalone via /blog notebooklm or internally from blog-write and blog-researcher for source-grounded research context. Falls back gracefully when not configured. Use when user says "notebooklm", "notebook", "query notebook", "ask notebook", "notebook research", "source grounded research", "document query", "notebook library".
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 image generation and editing for blog content powered by Gemini via MCP. Generates hero images, inline illustrations, social preview cards, and OG images, and edits existing ones. Supports 6 domain modes (Editorial, Product, Landscape, UI/Web, Infographic, Abstract). Works standalone or internally from blog-write and blog-rewrite; falls back gracefully when MCP is unavailable. Use when user says "blog image", "generate hero image", "blog illustration", "edit blog image", "OG image".
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 audio narration of blog posts using Google Gemini TTS. Supports summary narration, full article read-aloud, and two-speaker podcast/dialogue mode with 30 voice options. Outputs MP3 with HTML5 audio embed code. Works standalone via /blog audio or internally from blog-write. Falls back gracefully when API key is not configured. Use when user says "blog audio", "narrate blog", "audio version", "text to speech", "tts", "podcast mode", "read aloud", "audio narration", "voice", "narration", "generate audio".
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 a Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.
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 maintaining sports field visualization or Tkinter GUI and standalone CLI integration with Matplotlib.
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。
Discovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid search use cases in Google Cloud. Use when users need vector search combined with structured SQL filtering, faceted attributes, semantic reranking, in-database AI validation, or serverless hosting across transactional relational databases, analytical data warehouses, or managed database engines. DON'T use this skill for simple keyword-only search, or when a standalone non-relational vector database is required.
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 any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
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。
Standalone testing skill — owns writing and running tests, verifying behavior, and two-pass TDD orchestration. Default mode analyzes changed scope and runs the relevant tests; `--unit`/`--integration`/`--e2e`/`--all` scope by test type; `--verify` reruns exactly the prior failures; `--all-phases <plan>` sweeps every completed phase for regression. `--tdd --prepare`/`--tdd --verify` bracket `ck:cook` for red-green TDD. Never edits production code, and blocks until a phase's `ck:quality` gate is APPROVED (except `--tdd --prepare`, which runs before any implementation exists).
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。
Standalone testing skill — owns writing and running tests, verifying behavior, and two-pass TDD orchestration. Default mode analyzes changed scope and runs the relevant tests; `--unit`/`--integration`/`--e2e`/`--all` scope by test type; `--verify` reruns exactly the prior failures; `--all-phases <plan>` sweeps every completed phase for regression. `--tdd --prepare`/`--tdd --verify` bracket `ck:cook` for red-green TDD. Never edits production code, and blocks until a phase's `ck:quality` gate is APPROVED (except `--tdd --prepare`, which runs before any implementation exists).
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。
Integrate PocketBase as a Go library using the github.com/castle-x/goutils/pocketbase (gopb) package to build single-binary full-stack applications. Use when building Go applications that need user authentication, embedding PocketBase into Go binary, registering custom API routes, managing default users, serving embedded SPA frontend, or deploying single-binary applications. NOT for using PocketBase as a standalone separate process.
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。