「distribution」の検索結果

Backlink / off-page SEO audit. Works WITHOUT a paid tool by default — it uses the Google Search Console Links report (your top linking sites, most-linked pages, and anchor text) plus any backlink export the user provides (Ahrefs / Semrush / Majestic / DataForSEO CSV). Analyzes referring-domain profile, anchor-text distribution (over-optimized / spammy patterns), most-linked pages vs. money pages (internal-linking opportunity), toxic/spam link signals, and link-building priorities. Use this skill when the user asks about backlinks, link building, off-page SEO, referring domains, anchor text, toxic/spam links, disavow, or their link profile. Trigger on: "backlinks", "backlink audit", "link building", "off- page SEO", "referring domains", "anchor text", "toxic links", "spam links", "disavow file", "who links to me", "link profile", "domain authority". NOTE: rich third-party metrics (DR/DA, full link index) require a paid data source; this skill is explicit about what it can and can't see without one.

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Processes and analyzes data with resident-kernel engines (DuckDB, Polars) and one-shot tools. Use for CSV/parquet/JSON analysis, group-by/join/aggregation, time series, distributions, cleaning, or plotting a dataset.

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Contribute a verified bug fix for LazyCodex, lazycodex-ai, omo-codex, bundled Codex skills, or upstream Codex CLI bugs. Opens a fork PR only for upstream openai/codex; LazyCodex-owned defects become a verified-fix issue on code-yeongyu/lazycodex (never a PR — that repo is a generated distribution mirror). Use when the user asks to fix a bug, contribute a bug fix, contribute to fix bug, open a PR for a bug, or debug and PR a LazyCodex/Codex defect.

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⚠️ CRITICAL USER EXPERIENCE-BASED SKILL - ALWAYS CONSULT BEFORE DATA PREPROCESSING ⚠️ Prevents catastrophic errors (88.9% error rate in V1.0 case study) through multi-level feature analysis, data leakage detection, and semantic validation. MANDATORY for: data preprocessing, feature engineering, standardization, normalization, interpolation, missing value handling, feature selection, or ANY data transformation task. Covers grouped time-series, cross-sectional, panel data. Detects: time travel leakage, causal inversion, ID misuse, semantic-numeric fallacies, distribution blindness. User's hard-won lessons from real project failures.

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Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).

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Identify domains, families, and sites in proteins; find all proteins in a family or sharing a domain; explore species distribution for a domain; annotate genomes with protein families and GO terms. InterPro combines 14 databases (e.g., Pfam, CDD) into one searchable resource. InterPro-N significantly expands annotation and sequence coverage with deep learning. Includes domain architecture (IDA) search.

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Azure Queue Storage SDK for Python. Use for reliable message queuing, task distribution, and asynchronous processing. Triggers: "queue storage", "QueueServiceClient", "QueueClient", "message queue", "dequeue".

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Azure Cosmos DB SDK for Java. NoSQL database operations with global distribution, multi-model support, and reactive patterns. Triggers: "CosmosClient java", "CosmosAsyncClient", "cosmos database java", "cosmosdb java", "document database java".

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Quality control and assessment for proteomics data. Use when evaluating proteomics data quality before downstream analysis. Covers sample metrics, missing value patterns, replicate correlation, batch effects, and intensity distributions.

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Quality control for pooled CRISPR screens. Covers library representation, read distribution, replicate correlation, and essential gene recovery. Use when assessing screen quality before hit calling or diagnosing poor screen performance.

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Analyzes cfDNA fragment size distributions and fragmentomics features using FinaleToolkit or Griffin. Extracts nucleosome positioning patterns, fragment ratios, and DELFI-style fragmentation profiles for cancer detection. Use when leveraging fragment patterns for tumor detection or tissue-of-origin analysis.

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Extract nucleosome positions from ATAC-seq data using NucleoATAC, ATACseqQC, and fragment analysis. Use when analyzing chromatin organization, identifying nucleosome-free regions at promoters, or characterizing nucleosome occupancy patterns from ATAC-seq fragment size distributions.

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Quality control metrics for ATAC-seq data including fragment size distribution, TSS enrichment, FRiP, and library complexity. Use when assessing ATAC-seq library quality before or after peak calling to identify problematic samples.

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Provide US dividend tax and account-location workflow for Kanchi-style income portfolios. Use when users ask about qualified vs ordinary dividends, 1099-DIV interpretation, REIT/BDC distribution treatment, holding-period checks, or taxable-vs-IRA account placement decisions for dividend assets.

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Use this skill to track institutional investor ownership changes and portfolio flows using 13F filings data. Analyzes hedge funds, mutual funds, and other institutional holders to identify stocks with significant smart money accumulation or distribution. Helps discover stocks before major moves by following where sophisticated investors are deploying capital.

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Use when the user asks to "design an employee advocacy program", "set up founder-led sharing", or "build a share kit for the team"; produces an advocacy program blueprint in two modes — participation-driven opt-in (default) or top-down assigned with its coercion and authenticity risks flagged — with a voluntary opt-in roster spec submitted as channel-registry proposal events, share kits with mandatory per-person variation, staggered human posting windows plus anti-pod guardrails (no coordinated identical reshares, no engagement rings), per-person material-connection disclosure lines per FTC and 《互联网广告管理办法》, and a Slack/Teams distribution spec. Not for paid creator campaigns — use campaign-planner. 员工倡导/创始人IP分享/内部分享计划/披露合规

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Use when the user asks to "amplify influencer content with paid media", "set up whitelisting or Spark Ads", "decide which posts to boost", "repurpose influencer content", "turn one video into multiple ads", or "build a UGC asset library"; produces (paid mode) a content-selection scorecard, a paid amplification strategy (whitelisting/boosting/dark posts), audience targeting, and a budget+optimization plan, or (repurpose mode) a rights-tracked content inventory, a 1-video-to-10+-asset repurposing map, per-format transformation specs, and a 30-day distribution plan. Not for gating whether a deliverable is publishable or FTC-compliant — use creator-content-auditor; not for the always-on brand posting calendar — use social-calendar-builder; not for drafting a net-new idea into platform-native packages — use social-creative-builder. 复用达人内容 / 内容放量.

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Critique a rendered screen's hierarchy — entry point, eye flow, weight distribution, and emphasis. Use when attention lands in the wrong place. For establishing hierarchy in new work, use `visual-hierarchy` (ui-design).

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Configures Amazon Route 53 to route traffic to a CloudFront distribution using a custom domain. Use when setting up DNS alias records, alternate domain names (CNAMEs), ACM certificates for HTTPS, and IPv6 support for CloudFront.

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Creates and automates custom image builds with EC2 Image Builder - Linux, Windows, and macOS AMIs, and container images to ECR. Covers the build IAM role, Amazon-managed and custom components, image recipes, infrastructure and distribution configuration (launch templates, SSM parameters, other Regions), one-off builds, recurring scheduled pipelines for golden AMI automation and OS patching, custom image workflows, and diagnosing failed builds. Applies when creating, automating, or scheduling AMI or container image builds with Image Builder, or when debugging a failed build. Not for launching instances from existing AMIs, AMI lifecycle/retirement, or general EC2 fleet management.

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Amazon Redshift is NOT PostgreSQL; corrects LLM mistakes; covers SQL, metadata, connectivity/auth, storage, query performance, and operations. Applies ONLY to Redshift (provisioned or Serverless). Pushes back on: CREATE INDEX, string_agg, pg_catalog, text type, SERIAL, stl_query. Triggers on: Redshift SQL, Redshift CREATE TABLE, Redshift COPY/UNLOAD, slow or suddenly slow Redshift query, EXPLAIN plan, queue wait, stale statistics/ANALYZE, result cache, Redshift permission denied, Redshift disk full, storage growth, snapshot/backup cost, ghost rows/bloat, VACUUM, spill to disk, distribution skew, Redshift system views, QUALIFY, PIVOT, MERGE, materialized views, Redshift Data API (Python/boto3), Redshift workload management (WLM), concurrency scaling, Redshift resize, Spectrum, awsdatacatalog, connection failures (SSL/TLS, ODBC/JDBC, connection limit), IAM/SAML federation, IAM Identity Center, datashares. Does NOT apply to: S3 policies, Athena, Glue/Iceberg outside Redshift, Aurora, RDS, DynamoDB.

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Excalidraw canvas toolkit for creating, editing, and refining diagrams on a live canvas. Use when an agent needs to (1) draw or lay out diagrams, (2) iteratively refine them by describing the scene and screenshotting its own work, (3) export/import .excalidraw files or PNG/SVG images, (4) save/restore canvas snapshots, (5) convert Mermaid to Excalidraw, or (6) perform element-level CRUD, alignment, distribution, grouping, duplication, and locking. Primary interface is the bundled CLI (npx -y mcp-excalidraw-server <command>) which auto-starts the canvas server; MCP tools and a REST API are equivalent alternatives.

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Generate editorial calendars for blogs with topic clusters, publishing schedules, content decay detection, freshness update plans, seasonal opportunities, content mix formula, template integration, and distribution scheduling. Plans monthly or quarterly calendars optimized for SEO topic authority and freshness signals based on content priority. Use when user says "editorial calendar", "content calendar", "blog calendar", "publishing schedule", "blog plan", "content plan", "what should I write".

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Generate detailed content briefs for blog posts with target keywords, content outlines, competitive analysis, recommended statistics, image and chart suggestions, word count targets, internal linking architecture, template recommendations (12 types), TL;DR drafts, evidence-backed section planning, information gain prompts, and multi-channel distribution plans. Briefs are optimized for Google rankings and AI citation visibility as part of SEO. Use when user says "content brief", "blog brief", "write brief", "SEO brief", "article brief", or "content requirements".

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。