> Create a Linktree-style bio link hub page as a single self-contained HTML file. "bio link", "link hub", "create my link page", "all my links on one page", "linktree alternative", "build a link page", "bio page for my affiliate links", "I need a link in bio", "make a page with all my links", "link aggregator page".
npx skills add https://github.com/Affitor/affiliate-skills --skill bio-link-deployer
Create a Linktree-style hub page that links all your affiliate content — blog posts, landing pages, social profiles, and product links — in one place. Output is a single self-contained HTML file with 3 theme options, mobile-first (90%+ bio link traffic is mobile), deployable anywhere.
S5: Distribution — The central hub that ties your entire affiliate funnel together. Put this link in your social media bios, email signatures, and anywhere you need one link to rule them all. Unlike Linktree, you own the page and pay nothing.
user_name: string # REQUIRED — display name or handle (e.g., "@alexcreator")
tagline: string # OPTIONAL — short bio under the name
# Default: auto-generated from link categories
avatar_url: string # OPTIONAL — URL to profile image
# Default: emoji placeholder based on niche
links: # REQUIRED — at least 3 links
- label: string # Display text (e.g., "HeyGen — AI Video Creator")
url: string # Destination URL
category: string # Group label (e.g., "Tools", "My Content", "Connect")
icon: string # OPTIONAL — emoji for visual (e.g., "🎬")
theme: string # OPTIONAL — "minimal" | "dark" | "gradient"
# Default: "minimal"
Chaining context: If earlier skills (S1-S4) were run in the conversation, use these Output Schema fields:
recommended_program.url + .name → add as "Featured Tools" linksposts[].platform → link to the user's social platform profilesproducts_featured[].url + .name → add as "My Content" links (blog posts)landing_page.filename or deployed URL → add as "Landing Pages" linksproducts_featured[].url + .name → add as product links if not already includedIf the user says "make me a bio link with everything we've done" — gather all products, blog posts, and landing pages from the conversation and organize them into categories.
Collect links from one of these sources:
Option A — User provides links directly:
Use the links array as-is. Ensure each link has a label, url, and category.
Option B — Gather from conversation context:
If prior skills (S1-S4) were run, collect:
Option C — User provides partial info:
Ask for missing required fields. Minimum: user_name + 3 links.
Organize links by category. Suggested category order:
Read templates/bio-link.html for the page structure and all three theme variants.
Apply the chosen theme:
Minimal (default):
Dark:
Gradient:
Set CSS variables in :root based on the chosen theme. Remove the other theme blocks from the template.
If avatar_url is provided, use an <img> tag. Otherwise, use the emoji placeholder div with an emoji matching the user's niche (default: 🚀).
Present the final output in this structure:
Part 1: Page Summary
---
BIO LINK PAGE
---
Name: [user_name]
Theme: [minimal/dark/gradient]
Links: [count]
Categories: [list]
---
Part 2: Complete HTML
The full HTML file in a fenced code block (html). Save as index.html (or links.html`) and open in any browser.
Part 3: Deploy Instructions
Read references/domain-setup.md and provide the deploy options:
---
DEPLOY
---
1. Save as `index.html`
2. Preview: open the file in your browser
3. Deploy (pick one):
- Netlify Drop: drag the file to https://app.netlify.com/drop (30 seconds)
- Vercel: `npx vercel deploy --prod` (needs Node.js)
- GitHub Pages: push to repo → Settings → Pages → main branch
4. Add to your social bios: paste the URL in your Instagram, X, TikTok, LinkedIn bio
5. Custom domain: see references/domain-setup.md for DNS setup guide
---
Before presenting output, verify:
If any check fails, fix the output before delivering. Do not flag the checklist to the user — just ensure the output passes.
output_schema_version: "1.0.0" # Semver — bump major on breaking changes
bio_link:
user_name: string # Display name
theme: string # Applied theme
html: string # Complete self-contained HTML
filename: string # Suggested filename (e.g., "index.html")
link_count: number # Total links on the page
categories: string[] # Categories used
deploy:
local: string # "Open index.html in browser"
netlify: string # Netlify Drop instructions
vercel: string # Vercel deploy command
github_pages: string # GitHub Pages instructions
Present the output as three clearly separated sections:
The HTML should be immediately usable — save as .html, open in browser, and it works. No build step, no dependencies, mobile-optimized.
User: "Create a dark-themed bio link page for @sarahcontent with these links: HeyGen (heygen.com/ref), Semrush (semrush.com/ref), My HeyGen Review (blog.com/heygen), Follow on X (x.com/sarah)"
Action: theme=dark, organize into 3 categories (Tools, Content, Connect), generate HTML.
User: "Make me a bio link page with everything we've done today"
Context: S1 found HeyGen, S3 wrote a blog post, S4 made a landing page
Action: Gather all URLs from conversation, auto-categorize, default theme=minimal, generate HTML.
User: "I need a link in bio page"
Action: Ask for user_name and links. Provide example: "What's your display name and what links do you want? For example: product URLs, blog posts, social profiles."
templates/bio-link.html — Bio link page template with 3 theme variants (minimal, dark, gradient). Read in Step 2.references/domain-setup.md — Hosting and domain setup guide for Netlify Drop, Vercel, GitHub Pages. Read in Step 3.shared/references/ftc-compliance.md — FTC disclosure for bio link pages (footer text). Reference in Step 2.shared/references/affitor-branding.md — Affitor footer HTML. Reference in Step 2.shared/references/flywheel-connections.md — master flywheel connection mapAfter 7 days: which link gets the most clicks? Is it your top affiliate product? If not, reorder links — put the money link at position #1. Check weekly and rotate based on performance.
> Next step — copy-paste this prompt:
> "Deploy my bio link page to GitHub Pages with a custom domain" → runs github-pages-deployer
conversion-tracker (S6) — deployed link hub URLs to track clicksgithub-pages-deployer (S5) — bio link HTML to deploylanding-page-creator (S4) — landing page URLs to add to link hubsqueeze-page-builder (S4) — squeeze page URLs for link hubwebinar-registration-page (S4) — registration page URLs for link hubconversion-tracker (S6) reveals which bio links get the most clicks → reorder links to put highest-converting at topBefore delivering output, verify:
Any NO → rewrite before delivering.
chain_metadata:
skill_slug: "bio-link-deployer"
stage: "distribution"
timestamp: string
suggested_next:
- "github-pages-deployer"
- "conversion-tracker"
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 affitor/bio-link-deployer 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.
The instructions reference npx.
Without those the skill loads but fails at the first command.