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Benchmark CodeGraph retrieval quality on a real codebase by comparing agent behavior with vs without CodeGraph. Use when the user runs /agent-eval or asks to test, benchmark, audit, or validate a codegraph version (the local dev build or a published npm version) against a language's 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。

Use when Codex needs language-server diagnostics, definitions, references, symbols, or rename safety checks in the current workspace.

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。

Thorough, file-cited technical debt audit across 9 dimensions using AST-grep (tree-sitter), grep, LSP, and language-native tooling. Produces TECH_DEBT_AUDIT.md with severity, effort estimates, and prioritized fixes. Use when asked for codebase health check, tech debt audit, architecture review, code quality assessment, or cleanup planning. Triggers: 'tech debt', 'technical debt', 'debt audit', 'code health', 'technical debt audit', 'codebase health check', 'find tech debt', 'debt analysis', 'audit code quality'.

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。

Searches and rewrites code by AST shape across 25 languages. Use when the target is a syntax pattern (every call/class/import shaped like X, a codemod, a YAML rule) rather than literal text; for plain strings, comments, or filenames, use rg.

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。

Applies strict, modern language practice (typed errors, exhaustive match, tests that can fail) for Python, Rust, TypeScript, and Go. Use for work on .py, .rs, .ts, or .go files.

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。

Runs a hypothesis-driven debugging loop across any language or binary, escalating to orthogonal oracle angles and locking the fix with a failing test. Use for crashes, silent failures, hangs, wrong responses, memory leaks, async misbehavior, or reverse engineering.

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。

Configures a language server so editor/agent tooling (diagnostics, go-to-definition, references, rename) works. Use when a project needs an LSP installed or wired, or a 'no LSP server configured' error appears.

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 and conversationally edit short videos with Google Gemini Omni Flash (`gemini-omni-flash-preview`). Use when: (1) iterating on a clip with natural-language edits instead of regenerating ("make the phone invisible, keep everything else the same"), (2) generating 3-10s 720p clips with synthesized audio, rendered on-screen text, or timecoded beats, (3) binding reference images to roles with <FIRST_FRAME>/<IMAGE_REF_N> prompt tags, (4) editing an existing uploaded video. Accessed via the `gemini_omni_video` tool using the project's GEMINI_API_KEY/GOOGLE_API_KEY — the same key as Imagen and Google TTS.

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 speech audio from text using HeyGen's Starfish TTS model. Use when: (1) Generating standalone speech audio files from text, (2) Converting text to speech with voice selection, speed, and pitch control, (3) Creating audio for voiceovers, narration, or podcasts, (4) Working with HeyGen's /v1/audio endpoints, (5) Listing available TTS voices by language or gender.

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, extract, and apply portable visual design systems via visual-style.md files. Use when: (1) Creating a visual-style.md design system from scratch, (2) Extracting a visual style from a website URL, video, or PDF brand guide, (3) Applying a visual style to HeyGen videos, HTML slides, Figma, or paper.design, (4) Browsing the gallery of pre-built visual styles (Swiss, Saul Bass, Game Boy, etc.), (5) User mentions "visual style", "design system", "brand style", or "style guide", (6) Styling a HeyGen video with a consistent design language.

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。

Rewrite AI-sounding text so it reads like the writer without changing what it says. Use when editing or reviewing prose for AI tells: not-X-but-Y contrasts, one-line closers, staged openers, forced triads, dashes everywhere, inflated claims, sales language, stock AI words, bold labels, or filler. Based on Wikipedia's "Signs of AI writing."

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, refine, test, validate, or list CLI-Anything harnesses for GUI applications in Cursor. Prefer slash commands /cli-anything, /cli-anything-refine, /cli-anything-test, /cli-anything-validate, and /cli-anything-list when available. This skill supports natural-language discovery of the generator; it does not replace those commands. Discovering already-published CLIs from CLI-Hub is a separate consumer skill (cli-hub-meta-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。

Applies medicinal chemistry filters for compound triage, using drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the medchem query language for library filtering.

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。

Predicts regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer activity, chromatin state, sequence-to-expression (log TPM), and de-novo gene annotation, plus a composite find-genes-then-predict-expression workflow. Use when the user has a gene symbol, a genomic region, or a DNA/FASTA sequence and wants any of these predictions, mentions Genomic Intelligence, genomicintelligence.ai, api.genomicintelligence.ai, or mcp.genomicintelligence.ai.

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。

Draft or restructure scientific manuscript arguments, sections, and initial-submission materials from author-provided evidence. Use for 论文写作、章节起草、论证重构、正文压缩、首次投稿材料. Use nature-polishing for language-only edits to existing prose and nature-response for post-decision correspondence.

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。

How to use the PSL syntax tree layers (green tree, red tree, strongly-typed AST classes) correctly. Use for any PSL-related work: PSL interpreters (contract-psl), helpers inside the psl-parser package, the language server, formatters, or anything else that consumes `parse()` output from @internal/psl-parser.

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。

Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in 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。

Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates 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。

Generates client SDK code, API wrapper libraries, request/response models, and language-specific usage patterns for any REST 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。

Build natural-language crypto/DeFi agents and EVM MCP plugins (Claude Code, Cursor, Codex, Gemini). Aomi turns prompts into wallet-signed txs on Ethereum, Base, Arbitrum, Optimism, Polygon, Linea — non-custodial, fork-simulated. 40+ apps: Uniswap, Aave, Lido, Morpho, GMX, Hyperliquid, Polymarket.

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。

Binance P2P trading assistant for natural-language queries about P2P/C2C market ads, the user's own P2P order history, order detail & appeal tracking, and advertisement publish & management. Use when the user asks about P2P prices, searching/choosing ads, comparing payment methods, reviewing P2P order history, checking order detail/appeal status, querying complaints, publishing/updating/managing P2P advertisements, or viewing merchant profiles. Do NOT use for spot/futures prices, exchange trading, deposits/withdrawals, on-chain transfers, or anything unrelated to P2P/C2C.

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。

Decides what information belongs on a resume or CV, what to leave off and in what order, and audits an existing resume against those norms. Covers every section (contact details, photo, summary, experience, education and GPA, skills, languages, references), candidate situations (new grad, career change, gaps, layoffs, veterans, academic, visa and more) and country and industry norms. Use when the user asks "what should I put on my resume", "what should I leave off", "should I include my photo / GPA / date of birth", "how do I show a gap", "summary or objective?", "how long should my CV be", "CV for a job in Dubai / Germany", "I'm moving to another country, what should I change", "what to put on my resume as a veteran" or "audit / review my resume". Works with pasted text or the Reactive Resume MCP server. For rewriting bullets use resume-bullet-writer; for fitting a resume to one job posting use resume-tailor; for building a new resume as JSON use resume-builder.

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, refine, validate, and render diagrams from natural language, notes, code snippets, schemas, tables, or existing diagram source. use for flowcharts, swimlanes, sequence diagrams, state diagrams, er diagrams, class diagrams, architecture/c4-style diagrams, dependency graphs, gantt charts, mind maps, user journeys, sankey-style flows, org charts, network graphs, and other visual models. supports mermaid by default, graphviz dot for complex graph layout, plantuml for uml-heavy engineering diagrams, and svg output when direct markup is more reliable.

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。

Chinese K-12 core-literacy course design for a single OpenMAIC classroom. Use when a teacher asks for 中小学课程、核心素养、素养导向、2022 课标、真实情境、任务群、表现性评价, or wants a grade-and-subject lesson designed around authentic tasks rather than content delivery. Covers Chinese, mathematics, languages, science, humanities, technology, arts, PE and labor education across primary, junior-high and senior-high stages.

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。