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概要と使いどころ
Context management engine for AI coding agents. Use when building agent memory systems, optimizing context windows, allocating token budgets, designing RAG pipelines for code, or managing persistent multi-session agent state.
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 leadership guidance for engineering teams, architecture decisions, and technology strategy. Use when assessing technical debt, scaling engineering teams, evaluating technologies, or making architecture decisions.
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。
Engineer growth systems: PLG motions, referrals, viral and retention loops. "design a referral program"
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 authoring a Relayflows flow (@relayflows/surface / @relayflows/sdk, the journal-based v2 engine — the CLI is `flows`, package versions 2.0.x) in TypeScript or YAML/JSON. Covers the three-rung ladder (run/llm/agent), the resident verbs (human/dispatch/done), verification gates, TypeScript vs YAML authoring, per-step cli/model selection and its resolution order, flows.json, and `flows check`/`run`/`resume` with their real refusal shapes and exit codes. Not for the older, unrelated `@relayflows/core` WorkflowBuilder engine (`.pattern('dag')`/.agent()/.step() chains) that `writing-agent-relay-workflows` and `migrating-persona-to-relayflow` cover — that's a different product despite the similar name.
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-level toolkit for modular Godot 4.7+ CLI automation and headless build orchestration. Use when you need to: (1) Build complex scene trees or UI layouts programmatically, (2) Automate expert 3D asset pipelines (glTF -> Collision), (3) Optimize procedural geometry headlessly (CSG -> Static Mesh), or (4) Engineer production-grade CI/CD pipelines. Set GODOT_PATH env var for custom engine location. Keywords: Godot CLI, headless, CI, export, builder, 4.7.
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-level toolkit for modular Godot 4.7+ CLI automation and headless build orchestration. Use when you need to: (1) Build complex scene trees or UI layouts programmatically, (2) Automate expert 3D asset pipelines (glTF -> Collision), (3) Optimize procedural geometry headlessly (CSG -> Static Mesh), or (4) Engineer production-grade CI/CD pipelines. Set GODOT_PATH env var for custom engine location. Keywords: Godot CLI, headless, CI, export, builder, 4.7.
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。
ComfyUI prompt engineering knowledge covering CLIP text encoding syntax, weight modifiers, model-specific prompting strategies, and best practices
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。
When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," or "free resource." This skill bridges engineering and marketing — useful for founders and technical marketers.
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。
Tests whether a scene is structurally worth generating before any shot is prompted — a five-element engine of Goal, Obstacle, Tactic, Reversal, and Value Shift. Use when the user has a scene, sequence, beat outline, or script and wants it audited or strengthened; when a sequence generates cleanly but lands flat and nobody can say why; when shots look good individually but the run of them does not build; or when the user asks 'is this scene working', 'what's weak here', or 'why doesn't this land'. Upstream of prompting — it decides WHICH shots deserve the credits, not how to write them. Pairs with higgsfield-character-design (who the characters are) and higgsfield-shotlist-director (turning the settled scene into shots).
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。
SEO·AEO·GEO·LLMO·NEO(네이버) 다섯 레인을 진단하고 직접 구현하며, 인용되는 콘텐츠를 계속 생산하는 서브 블로그·콘텐츠 운영 파이프라인까지 세팅하는 스킬. 사이트를 검색엔진·답변엔진·생성 AI·네이버 AI 브리핑이 인용하는 1차 소스로 만든다. "SEO 해줘", "AI에 인용되게 해줘", "네이버 노출 늘려줘", "llms.txt 만들어줘", "블로그 만들어줘/글 써줘", "콘텐츠 백로그·캘린더 잡아줘", "낡은 글 갱신해줘" 류 요청에 사용. Use for "audit my site's SEO", "get my site cited by ChatGPT/Perplexity/AI Overviews", "improve search visibility", "create llms.txt", "answer engine / generative engine optimization", "set up a blog that gets cited", "content backlog / calendar / refresh", and any AI-search-visibility request.
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。
Reverse-engineer successful affiliate strategies from competitors. Use this skill when the user asks about spying on competitors, researching what other affiliates promote, analyzing competitor affiliate sites, understanding how top affiliates in a niche make money, or says "what programs does X promote", "how does [site] make money", "what affiliate strategy does this site use", "spy on competitor affiliates", "reverse engineer affiliate site", "copy what works in my niche", "who are the top affiliates in X niche", "what content gets traffic in my niche", "competitor affiliate 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。
Reverse-engineer raw materials (Sparse idea, Dense idea, experimental log) from an existing AI research paper to build a benchmark case for evaluating paper-writing pipelines. Replicates the PaperWritingBench dataset construction procedure from arXiv:2604.05018 §3 / App. C. TRIGGER when the user asks to "build a benchmark case from this paper", "reverse-engineer raw materials", or "evaluate my pipeline against PaperWritingBench".
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。
One-shot efficiency audit of a file, diff, or whole repo across BOTH axes at once: over-engineered code (reinvented stdlib, needless abstractions, speculative config) AND bloated prose (verbose comments, padded docstrings, redundant doc sections). Neither a pure code-minimizer nor a pure prose compressor does both in one pass. That's the point. Ranked report, biggest saving first; changes nothing. Use when the user says "chisle audit", "/chisle-audit", "audit this for bloat", "what can I cut", "review this PR for over-engineering and verbosity".
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。
Hire one of the eight open source AI Employees (GTM Engineer, SEO/AEO, Web Dev, Social Media, Ad Manager, Sales, Customer Satisfaction, Chief of Staff) into a local folder, prove it runs, and hand over its install prompt. Also answers which one to hire first, how a hired employee runs on a schedule, how to direct it, how it improves from corrections, and how to upgrade it. Use when the user says hire an employee, install an AI employee, set up the GTM Engineer, names one of the eight, or asks how AI Employees work. It copies files and runs self tests only. It registers no schedule and sends nothing.
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。
Zero-config goal-to-tasks engine (the Atlas engine). Takes any goal (software, pentest, business, learning), runs adaptive discovery via brainstorming, generates a validated spec, parses into TaskMaster tasks, and hands off to execution. Use when user says "PRD", "product requirements", "I want to build", invokes /atlas, or wants task-driven development.
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。
Provides reverse engineering techniques. Use when the main job is to understand how a compiled, obfuscated, packed, or virtualized target works before exploiting or solving it, including binaries, APKs, WASM, firmware, custom VMs, bytecode, malware-like loaders, and anti-debug or anti-analysis logic. Do not use it when the vulnerability is already understood and the remaining task is exploitation; use pwn instead. Do not use it for pure web workflows, log or disk forensics, or standalone crypto problems unless reversing the implementation is the real blocker.
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。
Your software-engineering brain trust. Named personas across 11 cells covering cloud architecture, reliability/SRE/observability, data and storage, security, FinOps, languages and runtimes, systems programming, web and frontend…
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。
A complete marketing department in one skill. Website and landing-page audits with weighted 0-100 scores, copywriting with panel scoring and AI-slop removal, an 18-tactic ad hook engine, GEO/AEO for getting cited by ChatGPT/Perplexity/AI Overviews, paid-ads creative diagnosis and production briefs, email sequences, LinkedIn/X writing, launch playbooks, positioning and offer design, competitor teardowns, app store optimization, honest analytics and test design. Use for ANY marketing task — audit, write, rewrite, diagnose, score, plan, launch, position, price, analyze — whenever the user mentions marketing, growth, conversion, copy, ads, hooks, CPM, ROAS, SEO, GEO, email, social, landing pages, funnels, launches, competitors, brand, positioning, pricing, or app stores, or says "my landing page sucks", "nobody's converting", "why are my CPMs up", "AI doesn't recommend us", "write me 20 hooks". Route via the table inside; fan out subagents for multi-dimensional work. Not for pure engineering, legal, or finance.
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。
Growth engineering - PLG, referral, viral loops, onboarding optimization.
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。
Reverse-engineer and clone a website in one shot — extracts assets, CSS, and content section-by-section and proactively dispatches parallel builder agents in worktrees as it goes. Use this whenever the user wants to clone, replicate, rebuild, reverse-engineer, or copy any website. Also triggers on phrases like "make a copy of this site", "rebuild this page", "pixel-perfect clone". Provide the target URL as an argument.
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。
Engineer effective LLM prompts using zero-shot, few-shot, chain-of-thought, and structured output techniques. Use when building LLM applications requiring reliable outputs, implementing RAG systems, creating AI agents, or optimizing prompt quality and cost. Covers OpenAI, Anthropic, and open-source models with multi-language examples (Python/TypeScript).
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。
ALWAYS USE for test work that requires changes: write, add, generate, repair, or strengthen tests for existing code in xUnit, MSTest, NUnit, pytest, Vitest/Jest, Go, or another framework. Includes regression cases, failing or flaky tests, coverage-driven additions, and audit-then-fix requests. Focused work stays direct; broad or multi-stage work invokes test-engineer. DO NOT USE for only running tests, analysis-only audits, framework/platform migrations, a test blocked on a missing production seam (testability-obstacle), or MSTest API/configuration corrections that do not design new cases (writing-mstest-tests). Within an active test-engineer pipeline, reuse supplied guidance and do not re-enter this 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。
Analyze user-provided reference images and reverse-engineer high-fidelity AI image-generation prompts. Use when the user asks to recreate, imitate, reverse-engineer, or extract prompts from photographs, illustrations, 3D renders, products, characters, landscapes, typography, logos, posters, or other visual references. Do not use for requests that only require OCR or an ordinary image description.
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。
Entrypoint for managing Volcengine Flink (based on Apache Flink) workloads. Use it for developing and deploying streaming and batch jobs, diagnosing real-time issues (e.g., backpressure, checkpoint failures, OOM), troubleshooting resources, and performing SRE actions (stop/start/restart/scale/config changes). It intelligently routes requests to four specialized sub-skills and leverages flink-mcp for tool execution.
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。