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Use when using the Beehave addon — pure-GDScript behavior trees with composites, decorators, leaves, a blackboard, and a visual runtime debugger

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Technical SEO audit across 9 categories: crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, JavaScript rendering, and IndexNow protocol. Use when user says "technical SEO", "crawl issues", "robots.txt", "Core Web Vitals", "site speed", or "security headers".

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Google SEO APIs: Search Console (Search Analytics, URL Inspection, Sitemaps), PageSpeed Insights v5, CrUX field data with 25-week history, Indexing API v3, and GA4 organic traffic. Provides real Google field data for Core Web Vitals, indexation status, search performance, and organic traffic trends. Use when user says "search console", "GSC", "PageSpeed", "CrUX", "field data", "indexing API", "GA4 organic", "URL inspection", "google api setup", "real CWV data", "impressions", "clicks", "CTR", "position data", "LCP", "INP", "CLS", "FCP", "TTFB", or "Lighthouse scores".

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When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'ROI calculator,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' or 'buyer persona card.' For competitor battle cards and comparison pages, see competitor-alternatives. For marketing website copy, see copywriting. For cold outreach emails, see cold-email.

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When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," or "SEO health check." For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.

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When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," or "breadcrumb schema." For broader SEO issues, see seo-audit.

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The discovery surfaces outside the App Store app — your apps.apple.com product page ranking on Google, an owned landing page with a Smart App Banner, and the deal-site ecosystem that auto-amplifies price drops. Use when building a landing page, improving Google visibility for an app, planning a price-drop promotion, or auditing off-store discovery.

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This package performs differential pattern analysis for Ribo-seq data. It identifies genes with significantly different patterns in the ribosome footprint between two conditions. RiboDiPA contains five major components including bam file processing, P-site mapping, data binning, differential pattern analysis and footprint visualization.

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The epistack package main objective is the visualizations of stacks of genomic tracks (such as, but not restricted to, ChIP-seq, ATAC-seq, DNA methyation or genomic conservation data) centered at genomic regions of interest. epistack needs three different inputs: 1) a genomic score objects, such as ChIP-seq coverage or DNA methylation values, provided as a `GRanges` (easily obtained from `bigwig` or `bam` files). 2) a list of feature of interest, such as peaks or transcription start sites, provi

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TFBSTools is a package for the analysis and manipulation of transcription factor binding sites. It includes matrices conversion between Position Frequency Matirx (PFM), Position Weight Matirx (PWM) and Information Content Matrix (ICM). It c

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This R package supports interactive visualization of multi-channel images and segmentation masks generated by imaging mass cytometry and other highly multiplexed imaging techniques using shiny. The cytoviewer interface is divided into image-level (Composite and Channels) and cell-level visualization (Masks). It allows users to overlay individual images with segmentation masks, integrates well with SingleCellExperiment and SpatialExperiment objects for metadata visualization and supports image do

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The Model-based Analysis of ChIP-Seq (MACS) is a widely used toolkit for identifying transcript factor binding sites. This package is an R wrapper of the lastest MACS3.

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基于 TrailSnap（行影集）现有设计系统设计、实现和审查前端 UI。适用于 package/website 的新页面、组件、布局、主题、移动端适配与界面改版；纯后端任务和其他项目不适用。

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Expert knowledge for Azure Network Function Manager development including security, and configuration. Use when setting up NF Manager prerequisites, resource groups, managed identities, role assignments, or secure NF access, and other Azure Network Function Manager related development tasks. Not for Azure Firewall Manager (use azure-firewall-manager), Azure Virtual Network Manager (use azure-virtual-network-manager), Azure Virtual Network (use azure-virtual-network), Azure Virtual WAN (use azure-virtual-wan).

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Expert knowledge for Azure Import Export development including troubleshooting, limits & quotas, and security. Use when setting CMK via Key Vault, checking drive limits, validating prerequisites, or debugging Import/Export job failures, and other Azure Import Export related development tasks. Not for Azure Data Box (use azure-data-box-family), Azure Blob Storage (use azure-blob-storage), Azure Files (use azure-files).

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Build prospect lists where the prospect is already one hop from the client, and write the line that says so. Seven members, each with its own source. Current-customer alumni is the priority member - everyone who ever worked at one of the client's customers or case-study companies and has since moved on. Triggers on "warm intro", "who do we know at that account", "they used to work at our customer", "alumni of our case study company", "shared investor angle", "who is in the same city as our rep", "did they visit our site". Outputs warm_intro_line plus a per-member evidence column.

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META skill — build the largest possible qualified lead list for any request, end to end. Orchestrates discovery (Prospeo + GetLeads + Blitz + Google Maps + lookalike snowball from /list-expander), AI qualification with live-website verify, uncapped contact pull (GetLeads → Blitz → Prospeo), and provider emails (GetLeads/Blitz/Prospeo) validated with MillionVerifier before sending. Use for any "build me a list", "get me leads for X", "find everyone who...", client list request, or campaign list build. Starts with a 7-line intake brief; outputs to Postgres, Google Sheet, and/or CSV (asks which).

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Index and shared harness for the 19 signal playbooks. Each playbook turns one buying signal (new in role, raised a round, hiring surge, pricing page, tech on website, ...) into one copy-ready sentence you can drop into a cold email. Every playbook ships three ways to run it: as a Claude skill, as a Clay table built through a browser harness, and as a Clay workflow built from the clay CLI. Use when someone says "personalize this list", "what signal should I use", "build the Clay column for X", or names any of the 19 signals.

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Expand a hard-to-build niche list from ~10 known-good seed companies into a full qualified TAM. Seed fingerprinting (how do good-fit companies ACTUALLY show up in the company database's filters) → lookalike generation (Prospeo company_lookalike, Exa findSimilar, Parallel.ai entity search) → filter mining with a precision/volume scorecard → wide pull with auto-sharding → cheap-AI qualification → live-website verification → client transparency report. Use when a vertical list feels "too small" (medical groups, hedge funds, Medicare brokerages), when known good-fit companies don't show up in keyword searches, or when someone says "expand this list", "the TAM should be bigger", "find more companies like these".

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Autonomous cold email campaign launcher. Takes one target company domain, scrapes their website, generates an ICP with Claude, pulls matching leads via Prospeo, enriches emails + company descriptions, personalizes each lead with parallel Claude Code Task sub-agents (A/B/C variants), and uploads as a live Smartlead campaign. Uses local JSON files for state (no database required). Use for automated daily campaign launches after you have an initial `client-profile.yaml` from /icp-onboarding. Triggers on "auto-research", "launch an automated campaign", "daily campaign", "run the research loop".

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Finds a prospect company's own case-study or customer-stories page and pulls one named customer off it, so email 1 can open with "saw your work with Intercom". Triggers on "case study", "customer stories", "who are their clients", "saw your work with X", "name-drop one of their customers", "logos on their site". Outputs case_study_line, a short clause that finishes the sentence "Saw ...".

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Creates cold email copy through a stepwise confirmation process. Use when writing email campaigns, given a campaign strategy document, website, or client context. Confirms direction at each step before outputting final copy.

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Generates 15-25+ cold outbound campaign ideas with targeting strategies, AI personalization approaches, and value propositions. Use when planning campaign experiments for a client, given their website or business context.

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Find people actively engaging with competitor LinkedIn posts. Given a website URL, discovers competitors, fetches their company and employee posts, collects all commenters and reactors, and outputs a deduplicated CSV of engaged prospects. Use when someone wants to find leads from competitor engagement, build outreach lists from LinkedIn activity, or analyze who interacts with competitor content.

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。