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Makes a codebase propagate W3C baggage (the `baggage` header carrying `mirrord-session=<key>`) end to end, so mirrord HTTP filters, preview environments, and queue splitting can route a whole request chain to one developer's session. Detects existing OpenTelemetry, Datadog, or other tracing that can already propagate baggage and enables it; otherwise adds a small propagation layer. Covers inbound/outbound HTTP and gRPC, publishing to and consuming from Kafka, RabbitMQ, SQS/SNS, GCP Pub/Sub, Azure Service Bus, NATS, Redis Pub/Sub, BullMQ and Temporal, per-message context restore in consumers, and storage hand-offs such as a GCS signed URL upload that triggers Pub/Sub or an S3 presigned upload that triggers SQS. Ends with a report of every flow found and which ones still drop the header. Use when the user asks to propagate headers, baggage, tracestate, the mirrord session key, or trace context across services or queues, or when a mirrord filter matches the first service but not downstream services or queue consumers.

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Helps DevOps engineers configure mirrord Operator's Temporal task queue splitting feature end-to-end. Generates the MirrordSplitConfig and MirrordPropertyList Kubernetes CRD YAMLs, the matching mirrord.json split_queues section with message_filter and jq_filter, and Helm value guidance. Use this skill whenever the user mentions Temporal splitting with mirrord, Temporal task queue splitting, splitting a Temporal worker, configuring mirrord with Temporal or Temporal Cloud, routing Temporal workflow or activity tasks to a local worker, or troubleshooting Temporal splitting sessions. Also trigger on split_queues with queue_type Temporal, or connecting mirrord to a Temporal frontend. This is an alpha Team/Enterprise feature of mirrord.

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Helps users configure mirrord.json for database branching, enabling isolated database copies for safe development and testing. Use when the user wants to set up MySQL, MariaDB, PostgreSQL, MSSQL, MongoDB, Redis, DynamoDB, ClickHouse, Google Spanner, Amazon S3, turbopuffer, or generic branches, configure copy modes, connection sources, schema migrations, IAM authentication, or manage database branches.

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Helps users run multiple concurrent mirrord sessions from a single mirrord-up.yaml (compose-style multi-service local debugging). Use when the user mentions mirrord up, mirrord-up.yaml, mirrord up init, debugging several related microservices together, or managing multiple mirrord sessions' lifecycle in one command.

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Help users chaos test their app with mirrord: inject artificial latency or connection errors into a mirrord session's outgoing traffic via per-session chaos rules managed with the `mirrord chaos` CLI. Use when a user wants to add latency or delay to outgoing connections or a dependency (e.g. a slow database), simulate connection failures (reset, timed out, refused), test app behavior under degraded network conditions, or wire chaos rules into CI test runs. Always use this skill instead of the deprecated _experimental_.latency mirrord config option.

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Help users set up mirrord in CI pipelines for testing against real Kubernetes environments. Use when users want to run end-to-end tests, integration tests, or automated tests in CI using mirrord to connect to staging/shared clusters.

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Local SEO and Google Business Profile audit: diagnose why a business isn't ranking in the local pack / map results and produce a fix plan. Covers GBP completeness, NAP (name/address/phone) consistency across the site and citations, local pack and "near me" ranking factors, review velocity and responses, local landing pages, service-area pages, and LocalBusiness JSON-LD. Use whenever the user asks about local rankings, map results, Google Maps ranking, NAP consistency, store/branch pages, or multi-location SEO. Trigger on: "local SEO", "Google Business Profile", "GBP audit", "rank on Google Maps", "local pack", "map pack", "near me ranking", "NAP", "local citations", "my business isn't on the map", "why don't I show up on Google Maps", "store locator SEO", "multi-location SEO", "service area pages", or any location-based ranking question. For full-site (non-local) audits use /seo-analysis; for a single URL use /seo-page.

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Generate JSON-LD structured data markup for rich results in Google Search. Supports FAQ, HowTo, Article, Product, LocalBusiness, and multi-type schemas. Validates against Google requirements and provides implementation guidance. Use when asked to "add schema markup", "generate structured data", "JSON-LD", "rich snippets", "FAQ schema", "product markup", "add structured data to my page", "how to get rich snippets", or any structured data task.

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Manage your self-hosted Immich photo library through conversation: natural language and OCR search, geographic album curation, duplicate detection, people and faces, metadata repair, video frames and PDF photobooks. 94 MCP tools and 13 skills, tested live on Immich 2.x and 3.x. Install: claude plugin install immich-photo-manager

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一句话生成大师级海报、书籍封面、专辑封面和各类设计作品。无需懂PS、配色或艺术史，AI自动选择最佳风格（基于33+位传奇设计师）。支持多平台多比例：公众号封面(21:9)、小红书配图(3:4)、文章配图(16:9)、书籍封面(9:16)、专辑封面(1:1)、电影海报(9:16)。包含AI提示词优化、风格对比、图生图转换功能。触发词："Mondo风格"、"书籍封面设计"、"专辑封面"、"海报设计"、"读书笔记配图"、"公众号封面"、"小红书配图"、"文章配图"。One-sentence generation of master-level posters, book covers, album covers and designs. 33+ legendary designer styles with multi-platform aspect ratio support (21:9, 16:9, 3:4, 1:1, 9:16).

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Use when the user asks to "optimize meta tags", "write title tags / meta descriptions", "add Open Graph or Twitter cards", or "generate schema / JSON-LD" for FAQ, HowTo, Article, Product, or LocalBusiness rich-result candidates. Produces title/description options, an OG+Twitter block, and validated JSON-LD for the document head. Not for body copy — use content-writer; not for crawl/index technical issues — use technical-seo-checker. 标题优化/元描述/Schema标记/结构化数据

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Configures AWS Application Recovery Controller (ARC) for operational resilience: routing controls with safety rules for cross-Region failover, and zonal shift / zonal autoshift for AZ-impairment recovery. Applies when setting up failover routing, configuring safety rules, enabling zonal shift, or configuring zonal autoshift with practice runs. Also applies when shifting traffic out of a specific Availability Zone (AZ) for an ALB/NLB or other resource. For a broader "an AZ is impaired, what is my response across services" question, see aws-resilience-lifecycle. Does not apply to Resilience Hub setup or FIS experiments.

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Provisions, scales, and operates Amazon EC2 virtual-machine workloads: instance-type selection (Graviton/Arm64, burstable T credits, GPU, instance store vs EBS), launch templates, Auto Scaling groups (scaling policies, instance refresh, mixed instances, Spot, warm pools, lifecycle hooks), IMDSv2, placement groups, Elastic IPs, AMI lifecycle, and Systems Manager fleet operations (Session Manager, Run Command, Patch Manager). Applies to EC2 instance and fleet questions, InsufficientInstanceCapacity, CPU-credit/surplus charges, IMDSv2 401s, instances stuck in Pending:Wait, ASG not replacing unhealthy instances, status-check failures, SSH refused/timed out, or instances missing as SSM managed nodes. For a single secure instance launch, the launching-ec2-instance-with-best-practices skill is more appropriate; for instance profiles, see setting-up-ec2-instance-profiles; for Image Builder, see amazon-ec2-image-builder. Does NOT cover Lambda, ECS/Fargate, EKS, VPC/ALB/NLB design, or IAM policy authoring.

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Generate radial plots (Radial Plot/Galbraith Plot) for heterogeneity analysis. Visually assess heterogeneity across studies by displaying the relationship between standardized effect sizes and precision. Input: Meta-analysis data in CSV format; Output: Radial plot PNG and data CSV.

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Creates an elegant, realistic Vinyl Record Player animation component for Remotion. Use when needing a music player UI, album showcase, or audio-visualizer interface in a video. (Keywords: 黑胶唱片, 音乐播放器, 唱片机, 专辑展示, 音频可视化)

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Maps intelligence for local SEO — geo-grid rank tracking, GBP profile auditing via API, review intelligence across Google/Tripadvisor/Trustpilot, cross-platform NAP verification (Google/Bing/Apple/OSM), competitor radius mapping, and LocalBusiness schema generation from API data. Three-tier capability: free (Overpass + Geoapify), DataForSEO (full intelligence), DataForSEO + Google (maximum coverage). Use when user says "maps", "geo-grid", "rank tracking", "GBP audit", "review velocity", "competitor radius", "maps analysis", "local rank tracking", "Share of Local Voice", or "SoLV".

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。

Maps intelligence for local SEO: geo-grid rank tracking, GBP profile auditing via API, review intelligence across Google/Tripadvisor/Trustpilot, cross-platform NAP verification, competitor radius mapping, and LocalBusiness schema generation. Three tiers: free (Overpass + Geoapify), DataForSEO, and DataForSEO + Google. Use when user says "maps", "geo-grid", "rank tracking", "GBP audit", "review velocity", "competitor radius", or "SoLV".

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Predicts protein-coding gene structures (exons, introns, UTRs) in eukaryotic genomes with BRAKER3 (RNA-seq + protein evidence), BRAKER1/BRAKER2, GALBA (protein-only), Funannotate (fungi), GeMoMa (homology projection), or Helixer/Tiberius (deep-learning ab initio). Covers the evidence-first tool decision, mandatory soft-masking, the training-set-quality-dominates principle, OrthoDB clade-partition selection, the one-isoform-per-locus and missing-UTR traps, merge/split errors, and reference bias against orphan genes. Use when annotating a newly assembled eukaryotic genome, choosing a gene-prediction pipeline based on available evidence, or diagnosing a poor annotation.

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Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream tools.

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Use when a task involves game textures or materials through the Scenario MCP: seamless or tileable textures, themed texture packs (brick, wood, stone, floors, hand-painted), PBR materials (albedo, metallic, roughness, normal) on 3D assets, retexturing a mesh, material iteration from reference images, texture upscaling that must preserve tiling, or sizing textures for game engines. Keywords: seamless texture, tileable, PBR, material, retexture, texture upscale, surface.

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Pick the right LLM for CONTRACT DRAFTING — generating, redlining, or rewriting contract language from instructions. Vendor-neutral routing grounded in mid-2026 legal benchmarks (legalbenchmarks.ai Contract Drafting). Asks up to 4 quick questions (cost, speed, accuracy/ stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model should I use to draft this clause/agreement", "best AI for drafting contracts", "route this drafting task", or is about to generate/redline contract text and hasn't fixed a model.

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Pick the right LLM for LEGAL INFO EXTRACTION — pulling facts, clauses, dates, parties, obligations, and structured fields out of contracts and legal documents. Vendor-neutral routing grounded in mid-2026 benchmarks (legalbenchmarks.ai Info Extraction; CUAD/MAUD/ACORD). Asks up to 4 quick questions (cost, speed, accuracy/stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model should I use to extract clauses/data from these documents", "best AI for contract data extraction", "route this extraction task", or is about to pull structured fields from legal docs without a fixed model.

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Pick the right LLM for LEGAL RESEARCH & ANALYSIS — issue-spotting, rule application, case/statute analysis, memos, and multi-step agentic research. Vendor-neutral routing grounded in mid-2026 benchmarks (Vals AI LegalBench across 124 models; Harvey Legal Agent Benchmark for agentic work). Asks up to 4 quick questions (cost, speed, accuracy/stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model for legal research / case analysis / a memo", "best AI for legal reasoning", "route this research task", or is starting legal analysis without a fixed model.

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。

Maps intelligence for local SEO — geo-grid rank tracking, GBP profile auditing via API, review intelligence across Google/Tripadvisor/Trustpilot, cross-platform NAP verification (Google/Bing/Apple/OSM), competitor radius mapping, and LocalBusiness schema generation from API data. Three-tier capability: free (Overpass + Geoapify), DataForSEO (full intelligence), DataForSEO + Google (maximum coverage). Use when user says "maps", "geo-grid", "rank tracking", "GBP audit", "review velocity", "competitor radius", "maps analysis", "local rank tracking", "Share of Local Voice", or "SoLV".

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。