「ema」の検索結果

Comprehensive SEO analysis for any website. Full site audits, single-page analysis, technical SEO (crawlability, indexability, Core Web Vitals with INP), schema markup, E-E-A-T content quality, image optimization, sitemap analysis, GEO for AI search, local SEO, and strategic planning. Uses Wove browser tools for real-page execution. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "structured data", "local SEO", "page speed".

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。

Drive web pages through the caveman-browse MCP tools (browser_snapshot, browser_act, browser_eval, browser_recover). Use whenever interacting with a web page, dashboard, or form through caveman-browse — it teaches the snapshot→act→verify loop, query-first discipline on large pages, and when to recover exact bytes.

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 transactional or notification emails via the Resend API — text and HTML content, multiple recipients, CC/BCC, reply-to, and file attachments. Single Python script with stdin pipe support. Triggers on 'send email', 'transactional email', 'email notification', 'Resend API', 'send via Resend'.

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。

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.

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。

Compute and analyze gematria (Hebrew numerical values) using standard, ordinal, and reduced methods. Covers word-to-number conversion, isopsephy comparisons, and interpretive frameworks. Use when computing the numerical value of a Hebrew word or phrase, comparing two words for shared gematria values, studying a biblical verse or divine name for numerical correspondences, or connecting a numerical result to its position on the Tree of Life.

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。

SWE-bench pipeline for A/B testing Grafema with Claude Code. Use when: (1) running SWE-bench experiments, (2) comparing baseline vs grafema conditions, (3) evaluating results, (4) debugging container issues.

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。

Fix node query issues in Grafema tests when nodes have numeric IDs instead of human-readable IDs, or when `type` field is undefined. Use when: (1) queryNodes returns nodes with numeric IDs like "52710336597754872375318185843222727675" instead of semantic IDs like "net:request#__network__", (2) node.type is undefined but node.nodeType has a value, (3) metadata is a JSON string instead of parsed object, (4) tests fail with "Cannot read property 'length' of undefined" after queryNodes. Covers RFDBServerBackend vs RFDBClient distinction and async generator handling.

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。

How to write a Grafema batch-mode plugin that reads the graph and filesystem, then writes new edges/nodes directly to RFDB. Use when: (1) need to add project-specific edges that generic analyzers can't produce, (2) need to read config files (JSON/YAML) and trace values into code, (3) implementing framework-specific resolvers (Django settings, Express routes, pipeline configs). Covers: grafema.config.yaml plugin config, RFDB field naming (src/dst NOT source/target), addEdges/addNodes API, RFDBServerBackend connection pattern.

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。

Write copy that converts. Use when writing landing pages, emails, sales copy, headlines, CTAs, social posts, cold emails, or any persuasive text. Triggers on 'copy', 'copywriting', 'sales copy', 'landing page copy', 'cold email', 'headlines', 'write me a page', 'make this convert', 'rewrite this copy', or any request involving persuasive writing. Three modes: Generate (write from scratch), Edit (improve existing copy with Seven Sweeps), Cold Email (outbound sequences). If someone has text that needs to sell harder, this is the 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。

Build a measured semantic core for a brand through official keyword APIs (Yandex Wordstat for RU, Google Ads Keyword Planner / Bing Webmaster worldwide, autocomplete everywhere), commit it as core.json plus a questions.csv, and hand that straight to an open-geo visibility run. Use when the user wants demand research, a semantic core, keyword volume, or "collect the questions and then measure visibility" — no browser and no manual keyword tool.

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。

Write cold outreach messages that actually get replies, on LinkedIn, in email, or in X (Twitter) DMs. Use this skill whenever the user wants to reach out cold to someone they don't know or barely know, including phrases like "write a cold DM," "cold email," "LinkedIn message to," "reach out to," "pitch [person]," "how do I get [person] to reply," "DM this investor/recruit/partner/podcast host," "email a founder/company I want to work for," "cold email for a job," "land a job at [company]," "reach out about a role," "follow up with someone who ghosted," or any request to draft a first-touch message to a stranger or near-stranger for fundraising, hiring, partnerships/BD, press/podcasts/speaking, or job-seeking. Trigger this even when the user just pastes a name, a role, and "help me reach out," and even when they don't say the word "cold."

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。

Investigates phishing email incidents from initial user report through header analysis, URL/attachment detonation, impacted user identification, and containment actions using SOC tools like Splunk, Microsoft Defender, and sandbox analysis platforms. Use when a reported phishing email requires full incident investigation to determine scope and impact.

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。

Executes authorized phishing simulation campaigns to assess an organization's susceptibility to email-based social engineering attacks. The tester designs realistic phishing scenarios, builds credential harvesting infrastructure, sends targeted phishing emails, and tracks open rates, click-through rates, and credential submission rates to measure human security awareness. Activates for requests involving phishing simulation, social engineering assessment, email security testing, or security awareness measurement.

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。

Create reproducible animated infographic GIFs from structured data or measured results, with audience-language labels, explicit timing semantics, representative-frame QA, and a static fallback. Use when asked for GIF生成, animated infographic, 動的インフォグラフィック, 結果が流れる図, animated benchmark, or a blog/SNS animation whose displayed metrics must remain traceable to source data.

Raise real concurrency in asyncio LLM batch scorers built on the OpenAI SDK (AsyncOpenAI, including OpenAI-compatible providers like DeepSeek). Use when: (1) raising an asyncio.Semaphore above ~100 produces no throughput gain, (2) a batch pipeline saturates near 100 in-flight requests despite a larger semaphore, (3) planning a high-concurrency campaign against a provider with no hard rate limit (DeepSeek v4-flash tolerates 2000+ in flight). Root cause: AsyncOpenAI's default httpx pool caps max_connections at 100, silently bottlenecking any larger semaphore — you must pass a custom http_client with httpx.Limits sized to the semaphore.

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。

Detect, validate, and generate Schema.org structured data with Ahrefs traffic prioritization. JSON-LD format preferred. Use when user says "schema", "structured data", "rich results", "JSON-LD", "markup", or "schema priority".

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。

Write recurring newsletter issues with a consistent format and POV using the Curiosity Gap (George Loewenstein) and David Perell's Online Writing framework. Different from one-off emails (use /content-writer or /email-nurture). Use when the user asks for a newsletter, weekly/monthly newsletter, "write this week's issue", recurring email, Substack issue, internal newsletter, or any periodic publication with subscribers. Reads brand voice and content library from knowledge/. For a nurture or lifecycle sequence, see email-nurture. For long-form thought leadership, see thought-leadership-writer. For the monthly plan, see social-calendar.

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。

Comprehensive SEO analysis for any website or business type. Full site audits, single-page analysis, technical SEO (crawlability, indexability, Core Web Vitals with INP), schema markup, content quality (E-E-A-T), image optimization, sitemap analysis, and GEO for AI Overviews/ChatGPT/Perplexity. Industry detection for SaaS, e-commerce, local, publishers, agencies. Triggers on: SEO, audit, schema, Core Web Vitals, sitemap, E-E-A-T, AI Overviews, GEO, technical SEO, content quality, page speed. Use this hub only when the SEO domain is clear and the requested workflow is not; otherwise use the exact retained leaf or 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。

Review Caveman Cloud evidence read-only: costs, Cave Score, Cave Plan, workflows, traces, latency, errors, compression, routing, and verified savings. Use when the user asks what Caveman found, where LLM spend goes, why cost or quality changed, which workflows need attention, or asks for a trace or analytics review. Prefer Caveman MCP tools; fall back to CLI JSON.

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。

Wire the current repository through the Caveman Cloud gateway so every LLM request is measured — cost, tokens, latency — with zero behavior change. Use when the user pastes the Caveman setup prompt, says "set up caveman", or wants LLM spend observability added to an app. Requires the gateway URL and a Cave API key (the setup prompt carries both).

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 Caveman's exact report-only repository observations into an operator-chosen optimization candidate with a paired baseline/candidate evaluation. Use when the user asks to inspect an optimization observation, evaluate a candidate change, or act on the current Caveman optimization report. Require a logged-in Caveman CLI connection and explicit approval; never infer money or actuation from a profile.

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。

Terse output mode — strips filler/articles/hedging, ~75% token reduction. Activate whenever: context is filling up, user says be brief/terse/caveman/less tokens, or CAVEMAN_TRIGGERED appears in context. Persists every response until CAVEMAN_RELEASED or user says stop/normal mode.

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 a BA or admin needs to document the Salesforce data model: creating field inventories, object relationship maps, ER diagrams, or analyzing field usage across objects. Triggers: 'data dictionary', 'document our data model', 'object relationship map', 'field inventory', 'ER diagram for Salesforce'. NOT for designing the model or choosing lookup vs master-detail — use data/data-model-design-patterns. NOT for generating the Mermaid or PlantUML diagram — use architect/salesforce-erd-and-diagramming. More trigger keywords: field inventory CSV, describe API, getGlobalDescribe, DescribeFieldResult, sObject describe, schema snapshot, schema drift, blank field descriptions, undocumented fields, field ownership, data dictionary review cadence.

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 Emacs as a channel. Opens an interactive chat buffer and org-mode integration so you can talk to NanoClaw from within Emacs (Doom, Spacemacs, or vanilla). Uses a local HTTP bridge — no bot token or external service needed.

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。