Skills de Claude Code · página 117

Detects price oracle manipulation and flash loan attack vectors in DeFi smart contracts. Classifies oracle trust models (Chainlink, TWAP, spot price, custom), identifies stale price risks, circular price dependencies, and flash loan atomicity exploitation patterns. Use when auditing DeFi protocols that depend on price data, oracle integrations, lending protocols, DEXs, derivatives, or any contract where flash loans could manipulate state within a single transaction.

Detects vulnerabilities in upgradeable proxy smart contracts including storage layout collisions, uninitialized implementations, function selector clashing, delegatecall context issues, and upgrade path safety. Covers Transparent Proxy, UUPS (EIP-1822), Beacon, Diamond (EIP-2535), and Minimal Proxy (EIP-1167) patterns. Use when auditing upgradeable contracts, reviewing implementation upgrades, analyzing delegatecall architectures, or verifying proxy pattern compliance.

Systematically detects all reentrancy vulnerability variants in smart contracts — classic, cross-function, cross-contract, and read-only reentrancy. Builds call graphs, verifies CEI (Checks-Effects-Interactions) pattern compliance, traces state changes relative to external calls, and identifies callback vectors through ERC-777/ERC-1155 hooks. Use when auditing contracts that make external calls, transfer ETH or tokens, interact with callback-enabled standards, or have complex multi-contract architectures.

Detects logic vulnerabilities in smart contracts by analyzing guard-state consistency patterns. Identifies functions that bypass security checks (require, modifiers) that other functions consistently apply. Uses the Consistency Principle — a contract is its own specification. Use when auditing smart contracts for missing access controls, inconsistent pause checks, logic bugs, forgotten modifiers, or when traditional tools report no issues but logic errors may exist.

Detects signature replay vulnerabilities in smart contracts — affecting 19.63% of signature-using contracts. Covers five replay types (same-chain, cross-chain, cross-contract, nonce-skip, expired-signature), EIP-712 domain separator verification, nonce management analysis, ecrecover edge cases (address(0), malleability, s-value), permit/permit2 safety, ERC-1271 contract wallet support, and meta-transaction security. Use when auditing contracts with ecrecover, ECDSA, EIP-712, permit, meta-transactions, multi-sig, or any off-chain signature verification.

Detects broken mathematical relationships between state variables in smart contracts. Automatically infers invariants (totalSupply = sum(balances), conservation laws, ratio constraints) then finds functions that violate them. Catches unauthorized minting, broken tokenomics, accounting desynchronization, and state drift. Use when auditing for state-state invariant violations, broken accounting, supply mismatches, desynchronized state variables, or conservation law violations in smart contracts.

Stage-aware prompt coaching, prompt improvement, lookback analysis, prompting habit feedback, and local reports about prompt quality for AI coding agents such as Claude Code or Codex.

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Expo React Native mobile app development with RevenueCat payments, AdMob ads, i18n localization, onboarding flow, paywall, and NativeTabs navigation

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Generates paste-ready Power Apps Canvas App YAML. Invoke when the user wants to replicate a UI mockup, improve an existing Canvas app screen, or build a new screen from a text description. Also invoke when the user asks to "improve", "redesign", or "generate YAML" for a Canvas app screen.

Show all your installed skills. Deprecated alias — use /janitor-report --brief.

Find new skills on GitHub or check a specific skill before installing. Use when the user wants to search for skills, evaluate a skill URL, check overlap with existing skills before installing, or compare a local skill against alternatives.

Automatically fix skill problems (safe preview first). Also use with --prune to find and remove broken symlinks, empty directories, and orphaned skills.

Check if a new skill overlaps with existing ones before installing. Deprecated alias — use /janitor-discover with a URL or path.

Full health check of all your skills in one report. Use when the user wants to check for errors, find duplicates, detect broken skills, or get a complete overview of skill health. Pass --brief for inventory only.

Search GitHub for new skills to install. Deprecated alias — use /janitor-discover (combines search + pre-install check).

Show how many context window tokens each skill consumes. Deprecated alias — use /janitor-value (which combines tokens with usage).

Show which skills you use. Deprecated alias — use /janitor-value (which now combines usage + token cost).

Show whether each skill is earning its context-window cost — combined tokens-used view sorted by waste. Use when the user asks 'are my skills worth it', 'what's my context budget', 'which skills are dead weight', or anything about skill value, token cost, or usage.

Delegates dbt and warehouse work to altimate-code, a specialized CLI agent with 100+ purpose-built data tools. USE THIS SKILL FIRST whenever the task mentions or implies: warehouse access (Snowflake, BigQuery, Redshift, Databricks, Postgres, MySQL, DuckDB), column-level lineage, downstream-impact analysis, dbt builds against a real warehouse, cross-database migration or validation, query cost attribution, schema diff, data parity checking, PII detection from sampled rows, incremental/SCD2/backfill verification, FinOps reporting, model documentation generation, query optimization, anomaly detection, dev-vs-prod diffing, or when the user says "altimate", "altimate-code", or "the data agent". Strongly preferred over Read/Write/Edit whenever the task touches live data, lineage, or warehouse state — consult before doing the work yourself.

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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.

Answer questions about code, architecture, and technical decisions — no implementation. Trigger on questions asking 'why', 'what does this do', 'what is the purpose of', 'explain', 'what's the difference', 'compare', or 'what are the tradeoffs' — even when referencing specific files, code snippets, or inline code. The key signal is the user wants to UNDERSTAND something, not change it. Do NOT trigger for requests to build, fix, plan, review, research, or add/modify code.

Implement, build, create, or add any feature, endpoint, page, component, or functionality. Use this skill whenever the user asks you to write new code or make code changes — whether it's adding an API endpoint, building a UI page, creating an export feature, wiring up a webhook, implementing a search/filter, or any other hands-on coding task. This is the default skill for all 'build this', 'add this', 'create this', 'wire up', 'implement' requests. Covers the full cycle: clarify requirements, plan if needed, write code, verify, and review. Do NOT use for pure research, debugging, documentation, or explanation — only when the user wants working code delivered.

Use when the user wants to save knowledge as a file so others don't have to rediscover it — \"turn this into a doc\", \"write this up\", \"document how X works\", \"we figured this out and want to capture it\", \"nobody should have to figure this out again\". Covers any request to create or update durable written artifacts: onboarding guides, runbooks, ADRs, API docs, architecture notes, postmortems, changelogs, setup guides. The trigger: user wants knowledge captured in a file for future reference, not just a conversation. Do NOT use when still making decisions (→ give-plan), just asking for explanation without a file (→ ask), or writing code (→ cook).

Investigate unexpected behavior and mysterious bugs. Use when the cause of a problem is unknown and the user needs to understand WHY something is happening — symptoms like: sudden unexplained changes in metrics or behavior, works locally but not in staging/production, inconsistent or intermittent failures, correct code producing wrong results, operations succeeding but having no effect, environment-specific failures, duplicate executions, stale data, or any \"why did this change?\" or \"why is this happening?\" situation. Covers infrastructure anomalies (cache hit rates dropping, latency spikes, queue behavior shifts) as well as code bugs. The key signal is confusion about root cause, not a request to implement a known fix. Do NOT use for feature requests, known fixes, planning, or documentation tasks.

Brainstorms and debates approaches, then drives toward an actionable decision. Use whenever someone needs a thinking partner for a decision they're facing: 'discuss', 'debate', 'brainstorm', 'weigh options', 'tradeoffs', 'should I do X or Y', 'help me decide', 'I'm torn between', 'sanity check my thinking', or 'what do you think about'. The user must be asking for help reasoning through a choice — not asking to build, fix, evaluate, plan, or modify something (even if the topic involves this skill itself). Picks the right decision lens, surfaces tradeoffs and blind spots, pushes back when reasoning is genuinely weak, and never implements.

Fetch up-to-date documentation for any library, framework, API, or service into context. Use when the user wants to look up API references, check function signatures or required fields, find feature-specific docs, or verify how an external tool actually works. Triggers for queries about third-party libraries like Stripe, SQLAlchemy, Tailwind, FastAPI, shadcn, Drizzle, Hono, Better Auth — any time the answer lives in official docs rather than in the project codebase. Use this instead of guessing from trained knowledge, which is stale.

Fix bugs and broken behavior when there is enough evidence to act on a repair path. Use for errors, crashes, incorrect results, API failures (500, 404, 403), CORS problems, database exceptions, broken rendering, duplicated or wrong data, off-by-one mistakes, timezone/date bugs, broken forms, config-caused runtime failures, and regressions. Trigger when the user wants the bug repaired and the conversation already contains a clear failing area, a reproducible failing test, a concrete error path, or a prior diagnosis to implement. Do NOT use for new features, pure explanation, architecture discussion, broad research, or bug reports where the main need is figuring out why the behavior happens — use diagnose for that.

Builds distinctive, production-grade UIs that avoid generic AI aesthetics. Use whenever the user wants to build, restyle, or give visual direction to any interface — pages, dashboards, landing pages, components, onboarding flows, mobile screens, or design systems — even without an explicit 'design' request. Also triggers for: picking an aesthetic direction, improving the look of a dull/generic existing page, adding visual personality, or choosing colors/typography. Includes a bundled design intelligence database for concrete guidance across web (React, Next.js, Vue, Tailwind) and mobile (React Native, Flutter, SwiftUI).

Use when the user wants a written, reviewable plan or spec produced before coding starts. Triggers on: mapping out changes without implementing, thinking through risks of upgrades or migrations, evaluating approaches before committing to one, writing specs for team review, phasing work into stages, or any request that explicitly defers coding ('don't implement yet', 'before we build'). The distinguishing signal is that the user wants a plan artifact — not implementation, not a conversational answer. MUST activates inside Claude's native plan mode to have a better planning behavior.

Specialized visual and multimedia processing tools. Use this skill whenever a task involves complex visual content — UI mockups, dense screenshots, design images, charts, artwork — where precise details like spacing, hex colors, font sizes, and component hierarchy need to be extracted accurately. Also use for: reviewing or auditing existing UI against designs, comparing screenshots for visual regressions, transcribing audio/video, extracting data from PDFs with complex layouts, and generating images. Trigger whenever the user wants to implement from a design, review or compare UI screenshots, analyze visual details precisely, describe artwork or aesthetic content, or process any media file (audio, video, PDF).

Generates a Claude Code configuration tailored to a specific project. Use whenever the user wants to prime a project, set up claude for a repo, bootstrap claude config, or re-prime/refresh an already-primed project (for example after `/prime-sync` pulled new starter content). Triggers on 'prime', 'prime this project', 'optimus-prime', 're-prime', 'refresh claude config', 'regenerate CLAUDE.md', 'set up claude for this repo'. Deeply analyzes the real codebase and builds project-specific skills, rules, and CLAUDE.md — not generic boilerplate. For ongoing config health checks and proposal review, use `self-evolve` instead.

Syncs Claude config between prime repo and target projects. Trigger on 'sync', 'prime-sync', 'push config', 'pull config', 'update prime', 'sync claude config'. Push mode deploys to targets; pull mode imports changes back.

Review code for quality, correctness, and fit. Use when the user wants judgment on code that already exists — their own changes, a teammate's patch, a PR, branch, commit, diff, staged changes, or one or more files to look over. Activate on requests like review, look over, sanity check, critique, code review, or 'is this good?' The key signal is that the user wants evaluation of existing code and its tradeoffs, not implementation, debugging, or explanation. This skill works independently, but when plans, specs, task artifacts, or prior discussion exist, use them to understand why the code exists before judging it.

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Use when the user wants to work on a Claude Code skill file (SKILL.md): writing one from scratch, testing whether an existing one works well, running evals or benchmarks, improving its instructions, or fixing why it isn't triggering. Triggers on: 'make a skill for X', 'test this skill', 'run evals on my SKILL.md', 'touch-skill', sharing a SKILL.md and asking if it's ready to ship. The key signal is intent to create, validate, or improve a skill — not just mention one. Do NOT trigger for general Claude Code questions, hook debugging, or CLAUDE.md configuration.

Use this skill for any Python backend work in this project: building FastAPI endpoints, writing service functions, defining Pydantic/SQLModel schemas, running Alembic migrations, or debugging 422 errors. Essential for authentication and authorization patterns — setting up get_current_user, is_superuser checks, admin-only guards, role-based access, and dependency injection chains like Depends(). Also covers middleware, background tasks, async SQLAlchemy sessions, ORM relationship loading, and request/response design. Activate whenever the question involves Python API code, FastAPI patterns, or backend architecture in this codebase. Not for frontend, Docker, CI/CD, or infrastructure.

ALWAYS activate when the user's query involves Docker in any way — even if it also matches other skills. If the words docker, Dockerfile, docker-compose, compose.yml, container, or image appear in the query, this skill MUST be used. Covers: writing or editing Dockerfiles and compose files, adding services (postgres, redis, etc.) to compose, volume mounts and data persistence, docker build failures (layer caching, npm install issues), healthchecks and service startup ordering (depends_on), environment variables in containers, port mapping, container crashes and exit codes (OOM/137), non-root users, multi-stage builds, image optimization, .dockerignore, and deploying to container runtimes. Takes priority over general implementation or debugging skills when Docker infrastructure is the subject.

Use this skill for ANY work involving React, Next.js, TypeScript, or Tailwind in the browser layer. This includes building components and pages, but equally covers debugging and fixing frontend issues: CSS/Tailwind classes not applying, form validation behavior, hydration mismatches between server and client renders, styling bugs, layout shifts, and rendering problems. Also use for refactoring components (e.g., splitting Server vs Client Components), data fetching patterns, state management, bundle optimization, and frontend tooling. If the problem involves what users see or interact with in a web browser — whether building, fixing, or refactoring — use this skill. Not for backend APIs, databases, infrastructure, or DevOps.

Rewrite existing text so it stops sounding AI-generated. Triggers on "humanize this", "un-ChatGPT it", "doesn't scream LLM", "strip the AI voice", or naming specific AI tells (em dashes, "it's not just X it's Y", "stands as a testament", "thrilled to announce", emoji-headed bullets, LinkedIn cringe). Works on any draft — blog posts, memos, READMEs, essays, PR descriptions — inline or in files. Keeps facts; changes voice. Do NOT use for writing new content, summarizing, translating, or pure-explanation requests with no draft to rewrite.

MUST use for ANY query mentioning packages, monorepo, workspace, catalog, turbo, turborepo, or pnpm in a multi-package context. MUST use when sharing config (ESLint, tsconfig, prettier) across packages, fixing build order between packages, adding new packages, scoping CI installs/caching to changed packages, or debugging pnpm catalog version resolution. This skill OWNS all cross-package coordination problems — even when they look like build, CI, config, or dependency issues. If two or more packages interact in the query, this skill applies. Takes priority over other skills when the problem spans package boundaries.

Detect common technical and organizational anti-patterns in proposals, architectures, and plans. Use when strategic-cto-mentor needs to identify red flags before they become problems.

Recommend architecture patterns (monolith, microservices, serverless, modular monolith) based on scale, team size, and constraints. Use when cto-architect needs to select the right architectural approach for a new system or migration.

Identify and challenge implicit assumptions in plans, proposals, and technical decisions. Use when strategic-cto-mentor needs to surface hidden assumptions and wishful thinking before they become costly mistakes.

Generate targeted clarifying questions (2-3 max) that challenge vague requirements and extract missing context. Use after request-analyzer identifies clarification needs, before routing to specialist agents. Helps cto-orchestrator avoid delegating unclear requirements.

Infrastructure and development cost estimation for technical projects. Use when planning budgets, evaluating build vs buy decisions, or projecting TCO for architecture choices.

Transform clarified user requests into structured delegation prompts optimized for specialist agents (cto-architect, strategic-cto-mentor, cv-ml-architect). Use after clarification is complete, before routing to specialist agents. Ensures agents receive complete context for effective work.

Deep expertise in ML/CV model selection, training pipelines, and inference architecture. Use when designing machine learning systems, computer vision pipelines, or AI-powered features.

Analyze incoming user requests to detect intent, request type (design/validate/debug/document), complexity level, and identify vague requirements or buzzwords that need clarification. Use when cto-orchestrator receives new requests that need classification before routing to specialist agents.

Generate phased implementation roadmaps with Epic/Story/Task breakdown, effort estimates, and validation checkpoints. Use when cto-architect needs to create actionable technical roadmaps from architecture designs.

Guidance for scaling systems from startup to enterprise scale. Use when planning for growth, diagnosing bottlenecks, or designing systems that need to handle 10x-1000x current load.

Recommend technology stacks based on project requirements, team expertise, and constraints. Use when selecting frameworks, languages, databases, and infrastructure for new projects.

Generate structured 8-section validation reports with verdict (GOOD/BAD/NEEDS MAJOR WORK), strengths, critical flaws, blindspots, and concrete path forward. Use after strategic-cto-mentor has completed validation analysis and needs to produce final deliverable.

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Use when the user asks to audit what's wrong with a project, "make it right", "看看项目出了什么问题", "为什么用户的需求还没上线", "为什么没提交App Store", "为什么没新build", or wants a holistic state-of-the-project check covering unmerged branches, stalled PRs, failed GitHub Actions, stale builds, plan drift (TODOS.md / ROADMAP), unreleased commits, and log errors. Runs read-only investigation, presents a grouped checklist, fixes only after explicit user confirmation. Aware of the Cathier iOS app workflow (Xcode + fastlane + auto-merge @claude PRs from in-app feedback).

Use when the user has a video + an SRT and wants the subtitles either burned into the pixels (libass, always-visible) or soft-muxed as a togglable track. Also handles the final composite step for the localization pipeline — burn subs, mix a dub track, and keep the original audio as a low-volume bed, all in ONE ffmpeg encode (no cascade). Verifies libass availability and auto-downloads a static evermeet ffmpeg build when Homebrew's stripped binary lacks it. Triggers — "烧字幕", "硬字幕", "burn subtitles", "burn-in subs", "embed subtitle", "soft mux SRT", "把字幕烧进视频", "做最终合成".

Use when the user complains about spam on his X/Twitter posts — 同城面付 / 寻固炮 / 线下上门 / 免费破处 这类引流号在他推文下刷的 emoji 垃圾回复 — and wants them removed. Covers the last 7 days (X recent-search window). Triggers — "把这些spam删掉", "清理X垃圾回复", "推文下面好多引流号", "clean spam replies", "/wjs-cleaning-spam".

Use when the user wants a 王建硕-style WeChat article (article.md) turned into a narrated short MP4 video — TTS voiceover via 火山引擎 Volcano TTS, HyperFrames CSS/GSAP animation per scene, subtle SFX, abstract watercolor background, full pipeline rendering to 1080×1920 portrait MP4 (30-90s). Triggers — "把这篇文章做成视频", "做一个解说视频", "讲解视频", "/wjs-converting-text-to-video".

Use when migrating a WordPress site to a Hugo static site on GitHub Pages from a WXR export (.xml) plus the wp-content/uploads folder — preserving /archives/<id>/ URLs, localizing images, and deploying via GitHub Actions. Triggers — "把 WordPress 迁成 Hugo", "wordpress 转静态站", "migrate WordPress to Hugo", "WXR to Hugo", "publish WordPress to GitHub Pages", "/wjs-converting-wp-to-hugo".

Use when the user has a video + a target-language SRT and wants the video to actually speak that language — generates a time-aligned TTS voice dub. Routes by voice ID — Volcano (豆包) TTS for Chinese, edge-tts neural for any language. Defaults to one voice (single-speaker); opt-in multi-speaker via visual diarization. Outputs `*_<lang>_dub.mp4` with the dub audio in place of the original. Final mixing (audio bed + burn-in) is handed off to `/wjs-burning-subtitles`. Triggers — "配音", "中文配音", "Chinese dub", "voice over this", "dub the video", "TTS this SRT", "different voice for each speaker".

吃一堑长一智 — 走完 5 步交互式反思（堑 → 自动输出 → 旧权重 → 新参数 → 替代动作），从「情绪复盘」推进到「行为训练」，把第一反应这一层 L3 权重练新。Use when 王建硕 reflects on a personal setback, mistake, or recurring pattern (反思, 复盘, 回顾, 总结教训, 吃一堑, 长一智, "这次又栽了", "怎么又这样", "为什么我总是…", "想开点都做不到", "知道道理但做不到"). For the user as a human, not for Claude's task post-mortems.

Use when the user has 2+ recordings of the same event (each with a `.sync.json` sidecar from wjs-syncing-multicam) and wants them combined into a single MP4 — auto-switching between cams second-by-second on audio energy, with optional picture-in-picture inset. Triggers — "auto-edit multicam", "做个剪辑", "切几个机位", "把这几个视频合成一个", "combine these angles", "PiP overlay".

Thin orchestrator for the end-to-end video localization pipeline. Routes to the four focused sub-skills — /wjs-transcribing-audio, /wjs-translating-subtitles, /wjs-dubbing-video, /wjs-burning-subtitles. Use when the user asks for full localization in one go ("帮我把这个西班牙语视频做成中文字幕+配音", "translate and dub this video", "做完整的本地化"). For any individual step (just transcribe, just translate, just dub, just burn), invoke the sub-skill directly — it's faster and the boundary is cleaner.

Use when the user wants to add an in-site feedback loop to a website repo — a floating "提个建议" button where allowlisted visitors submit suggestions that become a GitHub Issue, which GitHub Actions turns into an automatic code change via Claude Code, auto-merges and deploys, and records on a /_feedback dashboard with one-click revert. Triggers — "给网站加个反馈对话框", "提一句话就自动改网站", "装上反馈闭环", "feedback loop", "/wjs-looping-feedback".

Use when the user has a video's SRT subtitle file — a 王建硕 monologue / 讲解, OR a 对谈 / 访谈 where 王建硕 is one of the speakers — and wants to mine it into multiple standalone 微信公众号 articles, one article per distinct topic. Triggers — "把这个视频写成文章", "从字幕里挖文章", "这个 SRT 能写几篇", "把对谈写成文章", "/wjs-mining-articles <srt>".

Use when the user has one or more video clips and wants to add post-production on top — AI-generated cover as first frame, HTML/CSS captions synced to SRT, kinetic illustration overlays at hook moments, chapter chips, end-card CTA, or any other timed motion graphics. Most often used as the downstream of `/wjs-segmenting-video` — pick up where that skill stopped (raw cropped clip + per-clip SRT) and produce the upload-ready MP4. Backed by HyperFrames so everything compiles to ONE final encode — no cascade of re-encodes. Triggers — "加封面", "加字幕", "加动画", "加 CTA", "做后期", "post-production", "title card", "kinetic captions", "end card".

把一条平淡的中文 tweet/推文/帖子改写成"有真实事实支撑 + 带互动钩子"的高参与度版本,每次给 2-3 个不同钩子的版本,风格务必短、白、口语。只要用户贴出一条中文 tweet/推文/微博/帖子,并提到"润色""改写""优化""让它更有互动""涨互动""涨粉""提高回复""帮我把这条发得更好"等任何意图,就使用本 skill——哪怕用户没明确说"用 skill"。也适用于把某个观点/事实/日常做成"忍不住想回答"的提问帖或填空帖时。

Use when the user wants to set up automated daily promotion / marketing for their Claude Code skills — researching how top skills are promoted on marketplaces (ClawHub / openclaw / SkillsMP / agentskills.io), generating a per-skill marketing plan, auto-posting to X (Twitter) via xurl, and drafting community discussion posts (Reddit / HN / Discord). Triggers — "推广 skills", "营销 skills", "自动发推广", "每天自动推广", "skill marketing", "promote my skills", "/wjs-promoting-skills".

当用户想给自己的 Hugo 静态博客（如 maggiacito.com）新增或编辑帖子、管理类目、上传图片并发布上线时使用——对话式后台，说一句就改文件、commit、推送、自动部署，不需要任何 CMS/服务器。触发词：「发一篇博客」「给 Hugo 加文章」「写篇帖子到博客」「管理博客类目」「上传图片到博客」「博客后台」「/wjs-publishing-hugo」。

当用户想写或发布微信公众号文章时使用——他们给出零散思路、草稿或笔记，请你润色、生成题图和解释图，或准备上传到 mp.weixin.qq.com。触发词："写一篇微信文章"、"公众号"、"润色"、"题图"、"发公众号"、"/wjs-publishing-wechat"。

Use when the user wants to convert a video between horizontal and vertical orientations while preserving the inverted aspect ratio (16:9 ↔ 9:16, 4:3 ↔ 3:4, 21:9 ↔ 9:21). The skill crops a narrow band from the source and tracks the active speaker — the person whose mouth is moving — via MediaPipe face landmarks and mouth-aspect-ratio variance, so the talker stays in frame even when other people are visible. Triggers — "横转竖", "竖转横", "做成竖屏发抖音/视频号/小红书", "16:9 to 9:16", "make this vertical for Reels / TikTok / YouTube Shorts", "crop to portrait", "convert to landscape".

Use when the user has a long-form video (interview / lecture / podcast / conversation) and a transcript SRT, and wants to extract 3–6 stand-alone topical short clips from it. This skill ONLY cuts and crops — it produces raw clips + per-clip SRTs as a hand-off package for downstream post-production (`/wjs-overlaying-video`). Triggers — "切成几段", "分主题", "拆成短视频", "切片", "topic segments", "split into clips".

Use when the user has 2+ video / audio recordings of the same event captured by different devices (cameras, phones, separate audio recorders) and wants them aligned to a single common timeline. Outputs only a lightweight `.sync.json` sidecar per input — original files are never re-encoded. Triggers — "多机位同步", "对齐这几个机位", "match camera timelines", "sync these angles", "audio drift between cameras", "separate audio recorder", "Riverside / Zoom recording that needs to line up".

Use when the user wants to auto-syndicate their latest 微信公众号 article across social platforms — picks the newest un-syndicated article, extracts one core copy, auto-posts to API platforms (X / Bluesky / Threads / LinkedIn) and prepares a copy-paste outbox for manual platforms (Facebook / 小红书 / 即刻 / 知乎). Triggers — "分发文章到各平台", "同步到社交平台", "今天的文章发各平台", "/wjs-syndicating-articles".

Use when the user wants to teach / learn an English word as a video — turn a single English word into a self-contained HLS "supercut" lesson built from the mira video base. Stitches every season2 clip where the word is spoken (via the search-app API) into one .m3u8, prepended with a Claude-written bilingual word-intro card (word + IPA + 中文 gloss + usage, Volcano TTS) and appended with a 关注王建硕 CTA card. No MP4 burn. Triggers — "teach <word>", "讲讲 <word>", "学英语 <word>", "把 <word> 做成视频", "/wjs-teaching-english <word>".

Use when the user has audio or video and wants a timestamped transcript (SRT) in the source language. Routes by source language — Chinese defaults to Volcano (豆包) ASR; other languages (Spanish, English, Portuguese, French, Italian, Japanese, Korean, etc.) use OpenAI Whisper API with word-level timestamps and self-assembled cues. Outputs SRT with punctuation-bounded cues capped for on-screen reading. Triggers — "转写", "转成字幕", "做 SRT", "transcribe", "make subtitles", "speech to text", "出字幕".

Use when the user has an SRT (or transcript text) in one language and wants it translated to another, with punctuation-bounded re-segmentation so cues end at real sentence breaks. Simplified Chinese (zh-CN) and English (en) are first-class targets; other targets follow the same rules. Outputs a target-language SRT or bilingual SRT — no audio, no burn-in. Triggers — "翻译字幕", "翻成中文", "translate this SRT", "中英双语字幕", "把这个 SRT 翻译成 X", "bilingual subtitles".

Use when the user wants to post a daily X/Twitter tweet inspired by one of their recently-published 微信公众号 articles. Picks the newest article that hasn't been tweeted yet, drafts 3 tweet candidates from it (different angles — quote / metaphor / one-liner), posts the chosen one via xurl, records to history. Triggers — "每天发一个 tweet", "从文章里发推", "今天的 tweet", "/wjs-tweeting-from-articles".

Upload one or many videos to YouTube. Use when the user wants to "上传到 YouTube", "发 YouTube", "批量上传", "upload to YouTube", "post videos to YouTube", or to publish a finished `final/` directory of MP4s. Reads per-video metadata (title / description / tags) from a sibling `UPLOAD_META.md` file when present (the user's standard markdown format), or from command-line flags. Survives behind a SOCKS/HTTP proxy by using `requests` directly for the resumable upload (the stock `google-api-python-client` MediaFileUpload stalls under this user's proxy setup).

Use when 王建硕 wants to systematically improve his X (Twitter) content by iterating on the content-generation prompt (prompts/x/prompt.md, used by the every-6h tweet Action) and finding which prompt version produces the highest-reach tweets. Each prompt edit is a git-SHA-versioned, numbered experiment with a hypothesis; tweets are attributed to the version live at post time and judged on median impressions per tweet. Also mines per-tweet impression data for content-feature signals (angle / length / topic) that feed the next prompt edit. North-star = impressions per tweet. Triggers — "改 X 的 prompt", "X 内容改进", "哪版 prompt 最好", "什么内容 impression 高", "improve my tweets", "A/B test the X prompt", "/wjs-x-improving-content".

Use when 王建硕 wants to systematically grow his X (Twitter) followers by running numbered, A/B-testable growth experiments and tracking which ones actually work. Every action gets a number, a hypothesis, a target metric, a before-state (for rollback), and a verdict. The North-Star metric is the new-follower ÷ profile-visit ratio (conversion) — every profile change is judged against it. Daily it ingests the X Analytics CSV export, scores each running experiment, and recommends keep / rollback. Triggers — "涨粉", "增加 X 粉丝", "X 涨粉实验", "follower growth", "A/B test my profile", "今天的涨粉检查", "/wjs-x-increasing-follower".

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