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概要と使いどころ
Connect a site's existing WebMCP tools to AgentLane without rebuilding them. Use when a codebase already registers document.modelContext tools — natively or through any SDK — and the developer wants them visible in AgentLane, migrated onto @nekuda/webmcp-sdk with durable stable keys and verified to behave exactly as before.
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 building, debugging, or documenting Telegram bot polling flows that need safe agent routing, state tracking, and final-only replies without webhooks.
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。
Shell out to Claude Code CLI to invoke a second Claude session headlessly. Useful for cross-validation, second opinions, and isolated analysis without sharing current agent context. Requires Anthropic account.
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。
Verify fix commits address security findings without introducing new bugs or regressions. Analyzes diffs for anti-patterns like removed validation, weakened access control, reduced error handling, reordered external calls, and changed integer operations. Generates structured FIX_REVIEW_REPORT with finding status tracking.
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。
Set up nightly monitoring of subdomain changes, JS file diffs, new endpoints, and CVE matches against in-scope assets, with Discord/Slack/Telegram notifications. Use when the user has an active engagement and wants to be alerted to new attack surface without manual re-recon.
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。
Hunt GraphQL-specific vulns — introspection abuse, field-level authorization (IDOR), batched queries for brute force, alias-based rate limit bypass, deep query DoS, mutation injection, schema disclosure, suggestion leakage, CSRF via GET, and CSRF via POST without preflight. Use when a GraphQL endpoint is present.
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。
Phase 4 of 5 — implements tasks from TASKS-<N>-<slug>.md (with ARCH-<N>-<slug>.md as architecture-only context) using mode-appropriate verification (tdd, test-after, ui, checklist); pass 'auto' to run without stepping. Use only when the user asks to run Phase 4 or implement tasks from an ARCH doc — never trigger automatically from a coding 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。
Find the most valuable commercial insight and the monetization point closest to lawful revenue for a project, product, service, website, community, content account, open-source tool, or business idea. Use when a user asks how to monetize, who pays, why people do not buy, what to charge, whether to keep building, what to stop, what to do next, or asks to continue or deepen an earlier business analysis. Answer the user's actual question before asking for more information and carry the analysis forward without repeating it. When the buyer, purchased result, or delivery ability is unknown, do not select them from industry stereotypes; use explicit conditional candidates and an evidence-gathering next step. Not for investment advice, income forecasts, get-rich-quick schemes, or guaranteed results.
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。
RED-GREEN-REFACTOR for process documentation - baseline without skill, write addressing failures, iterate closing loopholes
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 security-conscious interfaces that protect users without frustrating them. Use when the user asks about MFA, password UX, breach notifications, trust indicators, secure forms, account recovery, or making security feel safe rather than scary.
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。
Adapt designs for narrow, medium, wide, embedded, or print web contexts without losing usability, hierarchy, or target sizing. Use when the user mentions responsive design, breakpoints, narrow layouts, viewport changes, touch-capable browsers, or cross-context adaptation.
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。
Rewrite text so it reads like a real person wrote it, not an AI. Auto-detects Russian vs English and applies the matching rule set. Use when the user asks to humanize text, remove the "AI smell", de-AI, or make AI output sound natural - especially for Russian. Russian requests count too - очеловечь, перепиши как человек, оживи текст, убери запах ИИ, сделай живее, звучит как робот, убери канцелярит. Also use when asked whether a text was written by AI - нейросеть писала?, похоже на ChatGPT?, видно ли, что это ИИ, человек или бот писал, did AI write this? - then check and report findings without rewriting. While installed, also keep your own Russian and English writing free of the quick-list stock phrases, silently; never edit the user's text unless asked.
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 after EZ_math_model coding has produced src/*.py and before packaging when code quality, reuse, vectorization, naming, or unnecessary complexity should be reviewed without changing 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。
Use when EZ_math_model runs in multi or hybrid mode and has two or more independent subtasks that can be assigned to subagents without shared files, shared state, or dataflow dependencies.
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 whether the knowledge base shelf-index is stale relative to the library files. Reports drifted entries without rebuilding. Designed to be invoked from environment validation or pre-push hooks as an opt-in check. Default mode is warning; strict mode fails with non-zero exit when any drift is detected.
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 wants to build, set up, or operate an AI "second brain" — a persistent memory vault (Obsidian-compatible Markdown) that lets an AI agent resume work without re-explaining context, remembers correction instructions across sessions, and auto-organizes raw material into structured knowledge. Trigger on requests like "build my second brain", "set up an Obsidian vault for AI", "give my AI persistent memory", or "make AI stop forgetting".
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。
Interact with 80+ websites and desktop apps from the CLI via Chrome session reuse — zero LLM cost, deterministic JSON/YAML/CSV output. Covers Twitter/X, Reddit, YouTube, HN, Instagram, Spotify, Amazon, LinkedIn, and more; also automates browser actions and registers local CLI tools. Triggers on 'opencli', 'CLI for website', 'scrape without API', 'browser automation', 'operate command'.
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。
Turn product photos and a minimal brief into verified, platform-adapted e-commerce detail-page systems, including product fact review, visual analysis, localized copy, 6-10 module story planning, policy-aware text-free image generation or real-photo routing, deterministic Pillow typography, platform-sized slices, long-page previews, manifests, and automated validation. Supports 淘宝/天猫/京东/拼多多/抖音/小红书/Amazon/AliExpress/Temu/TikTok Shop/eBay/Etsy/Shopify. Use when a user asks for 电商详情页, 商品详情图, 商详设计, A+ content, listing galleries, or a short-input workflow that turns product photos into ready-to-review commerce assets without inventing unsupported claims.
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。
Map user journeys, onboarding paths, entry points, first actions, trust points, accessibility risks, and SEO/LLM handoffs for public websites without redesigning the visual system. Use this skill when the user asks how new readers, returning users, project reviewers, community members, buyers, or AI agents should move through a site and what each page must make clear before layout implementation.
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 intentional internal link graphs for SEO, UX, and LLM-readable sites. Use this skill when the user asks for links between short briefs, longform articles, topics, projects, author pages, breadcrumbs, source trails, related stories, orphan-page checks, overlink checks, anchor intent, or validation that a link graph reinforces the canonical content model without creating duplicate story bodies or hidden links.
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。
Review public site content for editorial quality, source support, prompt residue, duplicate blocks, translation drift, hidden filler, and human usefulness before SEO or LLM-friendly publication. Use this skill when the user asks to quality-gate news briefs, longform explainers, blog posts, topic pages, project pages, translated content, or generated article drafts without changing the live publishing pipeline.
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。
Plan and record evidence-backed LLM and AI-search citation checks across approved assistant/search surfaces with timestamped queries, locales, modes, cited URLs, snippets, screenshots or transcripts, and caveats. Use this skill when the user asks whether ChatGPT, Perplexity, Claude, Gemini, Copilot, or another assistant cites a target site, but do not claim citation without direct evidence.
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 human-visible, machine-readable website layers for AI assistants, RAG, and agentic search. Use this skill when the user asks for llms.txt, LLM discovery plans, visible TLDR or direct-answer blocks, source trails, entity pages, markdown alternates, AI crawler policy, topic-to-URL maps, assistant-readable public content, or LLM-friendly architecture that must preserve canonical SEO strategy without hidden bot-only facts or duplicate story bodies.
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。
Find and score legitimate external authority and backlink opportunities as a dry-run register, using relevance, platform rules, risk, target-page fit, and explicit user approval gates. Use this skill when the user asks where links to a target site could be placed effectively, but never post, submit, DM, email, open PRs, or edit external accounts without separate explicit approval.
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。