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Plan and produce a content calendar — a month (or quarter) of blog posts, LinkedIn articles, and SEO content mapped to business goals, personas, and keywords. Generates briefs for each piece, optionally batch-produces all content with quality gates. Use when "content calendar", "plan blog content", "monthly content", "quarterly content plan", "what should we publish", "content strategy", "editorial calendar", or any request to plan multiple pieces of content over time.

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。

Full marketing audit — runs all relevant checklists against your product, site, and marketing in one go. Covers SEO, content, email, ads, social media, CRO, landing pages, technical SEO, and creative production. Produces a "state of your marketing" report with health scores per area and a prioritized fix list. Use when "marketing audit", "full audit", "audit everything", "marketing health check", "what's broken", "state of marketing", or any request to comprehensively assess marketing across all channels.

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。

Check the health and freshness of locally-stored Claude documentation. Use this skill when the user asks about documentation health, broken links, stale docs, freshness checks, or wants to validate that their local install is up-to-date and all URLs are reachable. Triggers on: "are my docs current", "check doc health", "validate documentation", "broken links", "stale docs".

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, register, and gate AI-callable tool endpoints using the OpenSea Tool Registry (ERC-8257) on Base. Scaffold HTTPS tools with JSON Schema interfaces, register them onchain, gate access via NFT ownership, subscriptions, trait gating, or x402 pay-per-call (USDC), and call gated tools. For querying OpenSea marketplace data use opensea-api 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。

On-call 轮值和 Runbook 维护时使用。适用于值班制度设计、操作手册编写、升级路径定义。融合 PagerDuty On-call + Atlassian Runbook。

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。

Answer Aperture Wallet questions from first-party product, security, network, release, app-screen, and Journal sources while enforcing explicit wallet-secret and no-transaction safety boundaries.

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。

Token transactions and wallet integration for XMTP agents. Use when sending USDC, creating transaction requests, or handling transaction confirmations. Triggers on USDC transfer, wallet calls, or transaction reference.

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。

Decompose dense codebase-wide, multi-document, PDF, and aggregation work even when the input fits the context window, following Recursive Language Models (Zhang, Kraska, Khattab, 2025). Use when the user asks to analyse all files, a whole repo, all docs, large PDFs, or to aggregate or multi-hop across scattered sources. Skip one file, one function, a single needle, or a one-page PDF conversion. Triggers: long context, context rot, large codebase, many files, all files, big document, multi-document, PDF, aggregate, summarize everything, codebase-wide, multi-hop, recursive, sub-agents, map-reduce.

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。

Trace execution time of Python method invocations in a live process with call stack visualization. Use this to see a hierarchical call tree showing which sub-calls are slow and where time is spent within a function.

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。

This skill should be used when the user asks to "buy token", "sell token", "swap token", "trade crypto", "check trade status", "query transaction", "scan tokens", "feed", "monitor chain", "query token", "token details", "check token safety", "list wallets", "show wallets", "my wallets", "AI scan", "AI扫链", "auto scan", "smart scan", "tweet scan", "推文扫链", "twitter scan", "onboarding", "get started", "check IP", "get IP", "IP whitelist", "查IP", "IP白名单", "launch token", "create token", "发币", "创建代币", "auto sell", "stop loss", "take profit", "trailing stop", "止盈止损", "移动止损", "holders", "top holders", "kol holders", "insider", "持仓", "持仓列表", or mentions trading on Solana/ETH/BSC/Base chains via XXYY. Enables on-chain token trading and data queries through the XXYY Open 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。

Builds CLO waterfall models with coverage tests, reinvestment criteria, and distribution allocation across tranches. Use when modeling CLO structures, analyzing OC/IC tests, or projecting tranche returns.

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。

Evaluates water rights valuation with seniority analysis, regulatory framework assessment, and allocation risk for resource investments. Use when analyzing water rights, evaluating water allocation, or assessing water risk.

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。

Measures implementation shortfall with paper portfolio comparison, delay cost attribution, and execution quality assessment. Use when measuring implementation shortfall, analyzing execution quality, or attributing trading costs.

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。

Post-implementation QA planning — independent of /review (the developer chooses whether to run them sequentially or in parallel), only when the change has a running surface worth driving. Interviews the developer to turn the specs and the diff into an executable QA specification (specs/qa/QA-<N>-<slug>.md) that /execute-qa runs. The agent drives browser and shell; the human steps in only at named handoff points. Use only when the user asks to plan manual QA — never trigger automatically.

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。

Render a dashboard of the current Claude Code session — message counts, token usage, cache read/write, dollar cost, context %, lines changed, cost-per-turn sparkline, and a tool-call histogram — parsed from the session transcript JSONL by a bundled bash script. One bash call, zero analysis, zero confirmation. Optionally pass a session id to inspect a different session. Use when the user asks for session stats, usage, token or cost breakdown, or a session dashboard.

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。

Optimize Docker build times using layer caching, multi-stage builds, BuildKit features, and dependency-first copy patterns. Applicable to R, Node.js, and Python projects. Use when Docker builds are slow due to repeated package installations, when rebuilds reinstall all dependencies on every code change, when image sizes are unnecessarily large, or when CI/CD pipeline builds are a bottleneck.

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。

Alluvial gold recovery using panning, sluicing, and classification. Covers site reading (geological indicators, stream dynamics, pay streak location), panning technique, sluice box operation, and responsible extraction practices. Use when prospecting in an area with known or suspected alluvial gold deposits, sampling a stream to test for gold presence, maximizing recovery during recreational panning, or assessing a site's gold potential before investing more effort.

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 a generative recipe DSL so agents emit small validated JSON documents and ONE audited interpreter renders them all — data, not code. Covers the N-artifacts threshold for choosing a DSL over bespoke code, designing roles as style slots so a single recipe renders unchanged in every output style, the validator gate (compile + bounds + real render in all styles, plus a --fast mode for corpus-wide sweeps), hand-authored seed recipes, and the emergent conventions that keep a corpus of hundreds consistent without per-item steering. Use when many similar artifacts (icons, status badges, diagram nodes, test fixtures) must be generated by agents, when per-item bespoke code is multiplying unreviewable code paths, or when a whole corpus must be re-rendered cheaply into new styles.

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。

Add an external probabilistic classifier to a decision path without letting it take the path over. Covers finding the externally-graded rows you are already logging, measuring the confidence separation between the overrides it got right and the ones it got wrong, choosing an operating point your data licenses, failing open at the call site, and proving the whole arrangement offline with no API key. Applies to any service returning a score you can order — TypeSafe AI's System One models (Jev) are the worked example. Most of the method transfers to a local model or a second heuristic, with the parts that do not called out where they arise. Use when a rule-based path is wrong often enough to hurt, when someone proposes replacing a heuristic with a model, when a confidence threshold needs a defensible value, or when an oracle already in production has never been graded.

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。

Next.js App Router routing primitives: file-based routes, dynamic and catch-all segments, route groups, parallel routes, intercepting routes, middleware, programmatic navigation, link patterns. Use this skill to: - Pick the correct dynamic segment syntax for the route shape. - Use route groups to organize without affecting URLs. - Implement parallel/intercepting routes for modal-style navigation. - Build effective middleware for auth, redirects, A/B tests. - Use Link and useRouter correctly. Do NOT use this skill for: - Data fetching per route (see nextjs-data-fetching). - General file conventions (see nextjs-conventions). - RSC vs Client (see server-component-patterns).

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。

Flask web framework conventions: app factory pattern with create_app(), Blueprint registration with url_prefix, MethodView for class-based API views, Marshmallow schema validation, WTForms for HTML forms, Flask-Login for session auth, flask-jwt-extended for stateless API auth, Jinja2 template conventions, error handlers, and extension initialization. Activated automatically by flask-plugin/stack.md. Use this skill to: - Structure Flask applications with the app factory and per-feature Blueprints. - Validate JSON request data with Marshmallow and HTML forms with WTForms. - Implement session-based auth with Flask-Login or token auth with flask-jwt-extended. - Render Jinja2 templates safely or return JSON responses for API mode. - Register global error handlers for consistent error responses. Do NOT use this skill for: - SQLAlchemy ORM model patterns and Flask-Migrate — see flask-plugin:sqlalchemy-patterns. - Python language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-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。

Concurrent investigation of independent failures. Use when multiple unrelated issues need parallel resolution.

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。

Parallel map-reduce bulk ingest for large source sets. Map phase dispatches read-only knowledge-extractor agents (≤N-wide, default Haiku) emitting per-source JSON extracts; Python routes extracts by target library file (fuzzy-merging new topics, pre-allocating new files, flagging oversized topics); reduce phase dispatches one agent-knowledge-updater per file (parallel, one writer per file); single shelf-index rebuild + one log.md entry. Resumable. Supersedes kb-ingest-batch.

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。

Send, read, and respond to Telegram messages as Claudicle via the @claudicle_bot Bot API. Use this skill when sending Telegram messages (text, Markdown, inline keyboards), building approval gates with tappable buttons, checking the shared inbox for unhandled Telegram messages, answering callback queries, managing Telegram memory context, or checking bot and listener status. Five purpose-built scripts (send, check, status, callback, memory) wrap the python-telegram-bot v22 polling adapter at ~/.claudicle/adapters/telegram/ with REST-based senders (no asyncio). Pairs with /telegram-respond for the cognitive pipeline and with mazkir-callback-watcher.py for the Mazkir approval gate.

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。