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Professional content generation system with a GSD-style phased workflow, integrated SEO optimization (claude-seo), and anti-AI auditing (humanizer). USE THIS SKILL whenever the user asks to write, draft, create, generate, or produce ANY content — including blog posts, articles, LinkedIn posts, Facebook posts, Twitter/X tweets or threads, Instagram captions, email newsletters, email campaigns or sequences, landing pages, product pages, web pages, sales pages, sales funnels, case studies, testimonials, product descriptions, or SEO metadata. Also triggers on: "/writer:discuss", "/writer:plan", "/writer:execute", "/writer:verify", "/writer:ship", "/writer:next", "/writer:profile-create", "/writer:profile-view", "/writer:profile-edit", "/writer:status", "/writer:help", "/writer:update" — or any request to manage a writer profile or create marketing materials. ALWAYS use this skill even for quick, casual content requests like "write me a LinkedIn post about X" or "draft a tweet thread." The profile and phased workflow produce significantly better output than ad-hoc generation.

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CTO-level architectural advisor for AI-native development. Use this skill whenever you encounter code design decisions, architecture discussions, system resilience questions, or any work touching: "architecture", "design", "scale", "dependencies", "state", "failure", "blast radius", "refactor", "migrate", "optimize", "resilience", "consistency", "observability", "bottleneck", "coupling", "monolith", "microservices", "distributed", "concurrency", "data flow", "system design", or any prompt suggesting code-first thinking when design-first thinking is needed. This skill integrates with Claude Code to review generated code for architectural soundness, define design systems via design.md, and guide teams toward CTO-level thinking. Trigger aggressively on architectural questions—this is where AI adds the most leverage.

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Multi-backend database security auditor. Audits Supabase, Firebase (Firestore/RTDB/Storage/Functions/Remote Config), MongoDB (self-hosted + Atlas), self-hosted PostgreSQL, and self-hosted MySQL for RLS/rules misconfigurations, exposed credentials, auth bypasses, MongoBleed (CVE-2025-14847), pgBouncer CVE-2025-12819, mysql_native_password drift, ghost auth, and storage exposures. Use this skill whenever the user mentions database security, RLS or rule audits, security review, penetration testing a vibe-coded app, checking if their DB is exposed, hardening a backend, fixing security rules, or auditing apps built with Lovable/Bolt/Replit/Cursor/Claude Code on any of these backends. Trigger on phrases like 'is my app secure', 'check my database', 'audit my Firebase', 'audit my MongoDB', 'audit my Postgres', 'audit my Supabase', 'is my DB exposed', or any cross-backend variant ('audit my full stack').

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Use when the user brings any fuzzy, half-formed, or interrupt-driven input — an order from a boss, a forwarded email thread, a ticket, a chat message, a "can you look into X", a raw idea — and it needs framing before work starts. Turns the input into a structured brief (Context · Desired outcome · Goal · Owner · Next step · Decision needed). This is the AIOS's front door; run most things through it first. Trigger on "/structure", "frame this", "what's the actual ask here", "structure this", or any vague task that lacks a defined outcome.

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Create or update a Wardley Map of how any domain delivers value. Maps the needs it serves, the capabilities involved, how each is evolving (genesis to commodity), and strategic plays. Applies to any domain, not only software.

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Interactive code simulation engine that spawns ghost personas to review your code before it ships. Each ghost walks through your code line-by-line from a different failure perspective: The Adversary (race conditions, double-submit, idempotency), The Enterprise Edge (business logic gaps, multi-currency, B2B tax exemptions, locale), Chaos Monkey (timeouts, partial failures, network partitions, OOM). Produces a chaos timeline, structured bug report with severity ratings, and three resolution tiers (quick fix, robust architecture, generated test suite). Use this skill whenever the user mentions code review, PR review, "find bugs", "what could go wrong", "will this break", "is this safe", "stress test", "edge cases", design review, pre-merge check, dry run, chaos test, or wants a second opinion on any code — even if they don't explicitly ask for "ghost personas" or "simulation". Also trigger when someone pastes a code snippet with any question about its correctness or safety.

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Use when writing or modifying code for s&box, sbox, the Facepunch sandbox engine, or any Source 2 game project in C#. Triggers on mentions of s&box, sbox, sandbox game, Facepunch engine, Source 2 game, `.sbproj`, `.razor` with `PanelComponent`, `@inherits PanelComponent`, `Sandbox.Component`, `GameObject` + `Components.Get<T>`, `Scene.Trace`, `CharacterController` + `.Move()`, `SkinnedModelRenderer`, `NavMeshAgent`, `[Sync]`, `[Rpc.Broadcast]`, `[Property]`, `INetworkListener`, `ISceneEvent`, `PlayerController` in C#. Also triggers on any file with `using Sandbox;` or `using Sandbox.UI;` that isn't Unity/Godot/Unreal. Writes idiomatic s&box C# components, Razor UI, and networking code; prevents Unity-pattern leakage.

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Use for any cap-table number, mechanic, or date before a founder signs, from a single SAFE, note or warrant described in chat or a quick 'is this dilution reasonable?' check to any draft or signed SAFE, note, term sheet, option plan, AoA, Carta XLSX, or spreadsheet. A single question gets a short cited answer in about 2–3 minutes; the full report, about 5–10 minutes, runs only when the founder shares documents or asks for it. Source-cited deterministic math (YC, NVCA, Cooley GO) for SAFE/note conversion, priced-round dilution, anti-dilution, option pools, warrants, MFN chains, dual-class voting, QSBS and Israeli §102 dates, and Israeli ↔ Delaware flips. NOT for waterfall modeling, cumulative dividends, RSUs, 83(b), 409A, SPAC, warrant repricing, or pure term definitions.

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Use on any core for first-run planning intake — Phase 0 runs the vendored BMAD-METHOD planning shelf, shared by every core, and Phase 1 (mining `04-prd.md` into intent records plus the Add-ons/sync-and-remote-entities decision) is full-stack-app's and pwa-app's shared procedure — identical mechanics, a different decision at step 5/8. Phase 0 also defines compressed intake, the path a user's explicit "just build it" choice takes on full-stack-app, pwa-app, authored, and copywriting cores: one batched round of questions in place of the shelf, writing a thinned archive at the same paths so Phase 1 (or, on copywriting, that core's own mining step), `ux-planner`, and the Re-entry pass all keep their documented source. Also use for the Re-entry pass, which mines new scope into additional intents without re-running the shelf, on any core with a module axis to add an intent to (full-stack-app, pwa-app, authored) — landing-page has none, so its own new-scope path runs through `hedgehog-landing-loop`'s Correction Protocol instead. Invoked by the `planner` agent, which decides the path; don't run standalone. landing-page runs this skill's Phase 0 on first run, then mines the same archive through `hedgehog-landing-loop`'s own planning-intake section, that core's counterpart to this skill's Phase 1. copywriting runs this skill's Phase 0 the same way (full or compressed), then mines the same archive through `hedgehog-copywriting-loop`'s own planning-intake section into a what/audience/register brief — no module axis, so its own new-scope path runs through that loop's Correction Protocol rather than the Re-entry pass below. An authored core runs this skill's Phase 0, then `hedgehog-core-design`, then this skill's Phase 1 mining against the designed layer sequence. A brownfield adoption (`hedgehog-adopt`) never runs this skill's shelf at all — the drivers BMAD elicits are already settled facts of a repo that already exists.

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Conduct an adaptive interactive interview on any topic and produce a structured markdown report, summary, or implementation plan. Use when the user says "interview me", "interview me about", "run an interview on", "help me think through", or wants guided discovery on any subject. Also triggers on "talk me through", "explore X with me", "help me plan Y", or "walk me through my thinking on Z" when the user wants a guided conversation rather than a direct answer. Applies broadly — career decisions, project ideas, product direction, personal goals, research questions, team problems — not just technical topics.

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Calculates stub equity value with subsidiary attribution, holding company discount, and sum-of-parts residual analysis. Use when analyzing stub values, evaluating holding company discounts, or identifying negative stub situations.

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Structures portfolio company engagement with board preparation, hiring support, business development, and follow-on strategy. Use when supporting portfolio companies, preparing board meetings, or coordinating investor resources.

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Enforce Biome formatting and lint discipline in this repository. Use when making any file edits, when asked to run format/lint, and immediately before any commit. Always execute `bun run lint` (from package.json), apply resulting fixes, and re-run until clean. Treat `bun run lint:links` as optional by default, and recommend it when files under `content/` are changed.

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Conversational profile builder. Produces validated JSON config files for any rootnode Skill that consumes profile-shaped configuration (handoff trigger check, mode router, critic gate, future Skills). Reads a target JSON Schema (draft-07), conducts a progressive-depth interview using plain-language questions, validates answers, and writes the resulting JSON to a destination path. Schema-agnostic — works with any profile schema conforming to draft-07. Use when a user needs to create, clone, or revise a profile and you do not want them hand-editing JSON. Trigger on: "build me a profile," "create a profile," "I need a profile for X," "set up my profile," "edit my profile," "clone the X profile," "walk me through making a profile." Do NOT use when the user already has a working profile and only wants to invoke the consuming Skill, when the schema cannot be located, or for non-profile JSON config work. Always validate before writing.

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Generalised autonomous optimisation loop — soft RLVR for any artifact a user can measure. Web runtime package: uses memory in this order: connector-backed, project-pack, none. Never assumes subprocess access or unrestricted local files. Use this skill whenever a user wants to iteratively improve an artifact — code, prompts, documents, configs, designs, content — by running structured experiments, evaluating results against a multi-dimensional rubric, and learning from each attempt. Triggers include: "optimise this", "keep improving until it's good", "run experiments on", "autoresearch", "iterate on this overnight", "try different approaches and pick the best", or any request implying repeated evaluate-and-improve cycles.

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Adversarial, security-first review of a pull request from an EXTERNAL or untrusted contributor — a fork PR, a first-time or unknown author, anyone without write access — before a maintainer merges it. Use this whenever you're reviewing, triaging, or deciding whether to merge a PR opened against tbh-meter by someone outside the maintainer team: 'review PR #123', 'someone opened a PR — is it safe to merge?', 'check this contributor's changes', 'can we take this fork PR?', 'is this contribution legit?'. This is supply-chain DEFENSE, not ordinary code review: every merged PR auto-updates onto every user's machine and ships a memory-reading .exe plus an unsandboxed Electron app, so the author and the PR description are UNTRUSTED and the diff is the only evidence. It posts its verdict as a real GitHub review — an inline comment pinned to each problematic line (via the pulls/reviews API), not just one summary comment. NOT for your own or a fellow maintainer's branch (use self-review for that), and prefer this over the generic review flow for anything coming from outside the team.

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TypeScript discipline for any JavaScript/TypeScript project (frontend + backend): strict mode, type design, generics, narrowing, error types, module resolution, tsconfig hygiene. Apply when the project has `tsconfig.json` and `typescript` in devDependencies. Stack-agnostic — referenced by every JS/TS framework plugin in the marketplace. Use this skill to: - Write types that catch bugs at compile time, not runtime. - Use generics, conditional types, and discriminated unions correctly. - Avoid `any`, `unknown`, and unsafe casts. - Match the project's tsconfig strictness level. - Type third-party libraries (with @types/* or declaration files). Do NOT use this skill for: - Plain JavaScript projects (no tsconfig.json). - Framework-specific type idioms (React component props, Vue defineProps, Angular signals — those live in framework plugins' own conventions skills). - tRPC/Zod runtime-validation specifics — handled by validation libs at the boundary.

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**雨哥（雨哥聊海外销售）出品**的海外销售公司背调与市场调研助手 —— 雨哥海外销售方法论金字塔「第 5 层 · 市场经营」的 AI Skill 化产物。基于「五看六定」经典市场分析框架（华为原版 + 雨哥改造版），输出标准化的市场调研报告，适用于客户拜访前调研、代理商签约前尽调、竞品季度跟踪、新市场进入决策、年度战略规划、面试求职准备等多种海外销售工作场景。 作者：雨哥 · 13 年海外销售实战 · 曾任普渡机器人亚太区负责人（年营收破亿 · 团队 5→50 人）· 海外销售培训头部 IP（累计付费客户 130+）。 触发方式：当用户说"帮我调研 XX 公司""做一下 XX 公司的背调""XX 公司的市场调研""调研 XX 在欧洲/北美/东南亚的市场""XX 公司客户拜访准备""XX 代理商尽调"时使用。 也在用户提到公司名 + 关键词（"调研""背调""尽调""市场分析""客户拜访""代理商谈判""竞品分析""go-to-market""GTM""面试""五看六定"）时主动触发。 This skill should be used proactively when a company research request is detected.

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Fires after fixing any non-trivial bug or regression. Asks: could the graph have caught this as a guarantee? Pairs with reflection-in-and-on-action — picks up after "earliest catchable signal" and asks the next question: was that signal expressible in graph? Triggers: (1) after any non-trivial bug fix is verified working, (2) after a regression report (something used to work, broke), (3) during step 6 (knowledge extraction) of the workflow, (4) when reflection-on-action surfaces a "would have been catchable" signal. Outcome is a triage decision (graph-reachable? rule expressible? rule sound?) and either a draft Linear issue + guarantee proposal, or a recorded "graph capability gap" note. Never auto-creates guarantees.

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Force `rust-embed` to re-embed assets from `$GRAFEMA_UI_DIST` (or any env-driven path) when cargo's incremental compilation skips the macro re-expansion. Use when: (1) you rebuilt the GUI bundle but the rust-server binary still serves the OLD bundle, (2) `cargo build --release` finishes in seconds (incremental hit) and `strings target/release/binary | grep <new-hash>` finds nothing, (3) any rust-embed pipeline where assets live outside the cargo source tree and are picked up via env var or symlink. Cargo only re-runs the proc macro when the rust file declaring `#[derive(RustEmbed)]` changes — env var changes alone don't trigger it.

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Apply the Minimum Sufficient Language (MSL) principle through the MSL Kernel to write anything a reader must act on. Bind the reader and what they already know, partition facts from the machinery that produced them, emit each admitted fact as an action, a verification, a judgment, or a state, and stop when every claim is checkable and the reader can act. Use for status updates, work-in-progress reports to your own user, closeout and convergence comments, tickets, pull request and review write-ups, incident and postmortem notes, emails, memos, and any draft for readers outside the work. Also use when the user says MSL, Minimum Sufficient Language, write this for stakeholders, drop the jargon, make this readable, or asks for a paste-ready draft.

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Compress any conversation into a portable JSON context graph for handoff to a new chat or LLM. Trigger on: "compress this chat", "save context", "new chat", "hand off", "transfer context", "too many tokens", "start fresh", "export conversation", "context graph", "continue in new session". Also trigger proactively when the user mentions starting over in a long session.

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Before any multi-step work with a stated goal — a feature, a bugfix spanning multiple files, a QA sweep, a doc draft + iterations, a multi-day investigation — create an ATO Mission instead of doing it via bare `ato dispatch` calls. A Mission persists the goal + the verifiable success criteria, lets the coordinator tick drive the work across days, captures every event in a structured audit trail (SQLite + markdown narrative), and integrates parallel agents' work via merge strategies. Complement to `ato-warroom` (the cross-family decision before you start) and `ato-review` (the post-code-diff review). Missions is where multi-step work LIVES; war-rooms are where decisions ABOUT it get made; reviews are where the resulting commits get vetted. Fires when: the work has more than one decision point, a verifiable end state, or runs across more than one session. Use it for any ATO development that doesn't fit in a single dispatch.

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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。