Build AI performance review assistance systems. TRIGGERS - Use when user needs help with ai-performance-reviewer related 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。
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概要と使いどころ
Build AI performance review assistance systems. TRIGGERS - Use when user needs help with ai-performance-reviewer related 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。
Build AI grant writing assistance systems. TRIGGERS - Use when user needs help with ai-grant-writer-system related 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。
Design AI financial advisory assistants. TRIGGERS - Use when user needs help with ai-financial-advisor related 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。
Design AI-assisted content creation workflows. TRIGGERS - Use when user needs help with ai-content-workflow related 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。
Build AI data analysis assistants with visualization. TRIGGERS - Use when user needs help with ai-data-analyst related 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。
Evaluate code (especially LLM-generated) for structural simplicity using Rich Hickey's "Simple Made Easy" framework. Use this skill whenever reviewing a PR, diff, or code snippet for accidental complexity — particularly when the code was generated by an AI coding assistant and line-by-line review isn't feasible. Also use when the user asks about complecting, simplicity vs. easiness, structural coupling, or concept deduplication. Trigger on phrases like "is this simple", "does this complect", "review for complexity", "structural analysis", or any reference to Hickey, Simple Made Easy, or grey-box 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。
Search and explore an Obsidian vault through the NoteBrain CLI (semantic search, tags, backlinks, connections, hidden links, boosted retrieval). Use it whenever the user mentions their notes, knowledge base, Obsidian vault, semantic search, finding connections or unlinked notes, or asks exploratory questions like "what do I know about X", "find notes related to Y", "what connects to Z", or "summarize my notes on W" — even when they never say NoteBrain, vector search, or ChromaDB.
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。
Detect and remove the tells of AI-generated writing in BOTH English and Spanish, and read back the evidence honestly. Use when the user asks to "de-AI" / "humanize" / "un-slop" a draft, to examine whether text carries the tells (delve, tapestry, "it's not just X, it's Y", "here's the thing", em-dash overuse, an assistant's own closing line left in the document), to compare documents for overlap, or mentions signs-of-ai / SignsOfAI. Backed by the SignsOfAI engine — for a measured 0–100 score, sentence-rhythm burstiness, originality, citations, a writer baseline or perplexity, hand off to that engine (web app, CLI or MCP server) as described below. It cannot determine who wrote a text and must never imply that it can.
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 creating, improving, or troubleshooting Claude Code subagents. Expert guidance on agent design, system prompts, tool access, model selection, and best practices for building specialized AI assistants.
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 production-ready AI agents using Google's Agent Development Kit with AI assistant integration, React patterns, multi-agent orchestration, and comprehensive tool libraries. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
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 guidance for building and editing n8n workflows with Synta MCP tools. Use for creating new workflows, modifying existing workflows, template discovery, node configuration, validation, and connection management in n8n.
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。
MATLAB R2026a data analysis workflow for tables, timetables, statistics, fitting, optimization-assisted analysis, visualization, report artifacts, and reproducible paper figures. Use whenever the user asks MATLAB to analyze data, plot results, fit models, process CSV/Excel/MAT files, or reproduce figures.
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。
MATLAB R2026a workflow for signal processing, DSP, image processing, computer vision, lidar, medical imaging, deep learning, and AI-assisted reproducible experiments. Use for filters, spectrograms, wavelets, object detection, segmentation, classification, training, inference, and generated figures.
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。
Facilitate sprint planning by organizing backlog items, estimating effort, balancing capacity, identifying dependencies, and producing a sprint commitment summary. Use when teams need structured sprint planning output. Do not use for strategic roadmap planning, annual budgeting, or product vision work.
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 Kanban flow metrics to identify bottlenecks and improve team throughput. Covers Cycle Time, Throughput, WIP, and Flow Efficiency using Little's Law and Theory of Constraints. Use when a team wants to optimize delivery flow or improve predictability. Do not use for sprint-based Scrum planning — use sprint-planning-assistant 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。
Assistant-behavior design skill for approximating a Claude-like analytical, careful, conversational style without claiming to be Claude or Anthropic. Use when the user asks to duplicate, emulate, adapt, or recreate a Claude-style "mythos" or persona for prompts, agent specs, writing style, reasoning discipline, safety posture, or UX behavior.
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。
Test Retrieval-Augmented Generation (RAG) systems for data poisoning, prompt injection via retrieved documents, and data exfiltration through manipulated context windows. Use this skill when assessing RAG-based chatbots, knowledge bases, enterprise AI assistants, or any system that augments LLM responses with external document retrieval. Covers document injection, embedding manipulation, knowledge base poisoning, and cross-document inference attacks.
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。
Test Large Language Models for direct prompt injection vulnerabilities where user input overrides system instructions, extracts system prompts, bypasses safety filters, or causes unauthorized actions. Use this skill when assessing chatbots, AI assistants, LLM-powered tools, or any application that processes natural language input through an LLM. Covers role-playing attacks, instruction hierarchy exploitation, multi-turn manipulation, and context window abuse for comprehensive AI security testing.
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。
Exploit AI assistants equipped with web-browsing capabilities or internal API plugins to perform Server-Side Request Forgery (SSRF). This skill details injecting prompts that force the LLM to request sensitive internal endpoints, such as underlying cloud metadata services or internal networks.
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。
Visual design verification loop for matching a goal PNG to a live render. Use when the user shares a design mock / goal image and asks to match the UI to it, asks to "iterate on this design" or "match this 1:1", or calls out visual drift in a previous UI iteration. Provides histogram color sampling, shape inspection (radius/border/shadow/bg-mode/fill-vs-context), computed-style checking on the live render, snap, and side-by-side diff. After every UI change the assistant MUST snap the live render and Read the snap with the Read tool before reporting the change done — skipping that is the
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 reviewing or improving frontend accessibility, semantic structure, keyboard support, focus management, ARIA labels, screen reader behavior, WCAG 2.2 issues, touch accessibility, or assistive-technology regressions; Chinese triggers include accessibility, accessibility, a11y, WCAG, screen reader.
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。
将课程资料(PPT/Word/PDF/截图)按章节生成深度知识清单、教授式详细讲解和交互式章节测试,帮助学生高效期末复习。
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。
Product-led growth and customer-base growth for B2B SaaS. Use this skill for self-serve funnel work (activation, time-to-value, free trial vs freemium, PQL definition, in-product upgrade moments, sales-assist triggers), for the self-guided interactive product demo that runs in front of the login wall (demo portfolio and flow design, gated vs ungated policy, demo seed data and privacy, keeping a published demo in sync with the shipping product, step-level demo analytics), and for growing revenue from existing customers (adoption, expansion, churn-save, the self-serve cancel flow and failed-payment recovery, renewal marketing, net revenue retention, and champion tracking: watching the people who bought and used you at each customer, confirming a job change from evidence, and running both plays a move fires, the seat they left and the account they joined). Also triggers on: PLG, product-led growth, activation, aha moment, time to value, free trial, freemium, PQL, product qualified lead, onboarding, self-serve, customer marketing, expansion revenue, upsell, cross-sell, churn, retention, NRR, renewal, cancel flow, cancellation flow, save offer, exit survey, pause subscription, dunning, failed payment recovery, involuntary churn, people keep canceling, champion tracking, job change signals, job change alerts, our champion left, our champion changed jobs, customer alumni, former customers who moved to a new company, interactive demo, self-guided demo, product tour, click-through demo, demo automation, demo library, should our demo be gated, ungated demo, demo without a sales call, our demo is out of date, demo shows the old UI, put a demo on our homepage, demo completion rate, demo drop-off, try before you talk to sales.
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 a task needs the judgment of a K-12 Education Administrator (principal/assistant principal/district administrator) — making a school-level policy or resource-allocation decision, handling a discipline or safety incident, evaluating a curriculum or staffing decision, or balancing competing demands from teachers, parents, students, and district requirements.
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。