Manage URL redirects. Use when: creating 301/302 redirects, auditing chains, fixing loops, or deploying via CMS MCP.
npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill redirect-manager
Manage URL redirects across the website. Create new 301/302 redirects, audit existing redirects for chains and loops, fix broken redirect paths, and deploy changes via connected CMS MCP. Covers site migrations, URL restructuring, and ongoing redirect maintenance. Redirect mismanagement is one of the most common causes of SEO traffic loss — chains dilute link equity, loops create crawl errors, and broken redirects return 404s for previously indexed URLs. This command provides systematic redirect lifecycle management from creation through auditing and repair.
yes (or an equivalent explicit approval). ANY other input — ambiguous, implied, partial, or absent approval — cancels the run.python "${CLAUDE_PLUGIN_ROOT}/scripts/approval-manager.py" --brand {slug} --action create-approval --data '{"risk_level":"<tier>","summary":"..."}' before executing, then python "${CLAUDE_PLUGIN_ROOT}/scripts/approval-manager.py" --brand {slug} --action mark-executed --id {approval_id} after the platform confirms success.The user must provide (or will be prompted for):
create (set up new redirects), audit (scan all existing redirects for issues), fix (resolve chains, loops, and broken targets found during audit), or bulk-import (import a redirect map from CSV or Google Sheet for migrations). Multiple actions can be chained (e.g., audit then fix)/old-blog/* to /blog/*), or regex patterns for complex matching. For audit and fix, source URLs are discovered automatically from the CMS301 (permanent — use for permanent URL changes, domain migrations, HTTPS upgrades, and URL restructuring) or 302 (temporary — use for A/B tests, seasonal content, maintenance pages, or geo-redirects). Default is 301 if not specifiedwordpress or webflow — must have the corresponding CMS MCP server connected. For WordPress, specify the redirect management method: Redirection plugin, RankMath redirects, Yoast Premium redirects, or .htaccess direct. For Webflow, the native redirect API is used~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply brand voice, compliance rules for target markets (skills/context-engine/compliance-rules.md), and industry context. Also check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load restrictions. Check for agency SOPs at ~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults.medium for individual redirect creation or small fixes (under 10 changes), high for bulk imports, migration-scale changes (over 10 redirects), or any deletion of existing redirect rules..htaccess modification (last resort, with backup). For Webflow: use the native 301 redirect API with bulk support for migrations. Handle CMS-specific constraints — Webflow's 301-only limitation, WordPress plugin-specific rule formats, and pattern-matching syntax differences.A structured redirect management report containing:
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Take indranilbanerjee/redirect-manager from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.