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Colter Fix

Generate the code.
Deploy in minutes.

Every gap gets generated code — WebMCP forms, JSON-LD, robots.txt, UCP manifests, and 15+ fix types — ranked by revenue impact.

Run a check firstView documentation
WebMCP form — generated by Fixhtml
<!-- WebMCP: Add to Cart (generated by Colter) -->
<form toolname="add-to-cart"
      tooldescription="Add a product to the shopping cart"
      toolautosubmit>
  <input type="hidden" name="product_id"
         value="{{product_id}}"
         toolparamdescription="The product identifier">
  <input type="number" name="quantity" value="1"
         min="1" max="99"
         toolparamdescription="Number of items to add"
         required>
  <button type="submit">Add to Cart</button>
</form>
What Fix generates

18 fix types across every protocol

Each fix includes generated code, deploy steps, expected score lift, and a copy-paste LLM prompt.

  • WebMCP6 commerce tools: search, add-to-cart, update-cart, remove, checkout, get-details
  • DiscoveryJSON-LD (Product, Organization, Breadcrumb), Open Graph tags, llms.txt, robots.txt
  • ProtocolsUCP manifest, ACP endpoints, MCP tools config, AGENTS.md, A2A agent card
  • SecurityHSTS, Content Security Policy, X-Frame-Options, X-Content-Type-Options headers
  • PlatformsShopify Liquid templates, WooCommerce snippets, static HTML, custom REST
  • GuidancePer-fix deployment instructions, expected score lift, LLM prompt for AI assistants
How it works

From gap to deployed in three steps

1

Scan

Run Check on your store. Fix identifies every remediable gap.

2

Generate

Platform-specific code for each gap, ranked by revenue impact. Copy-paste ready.

3

Deploy

Follow deploy instructions or one-click apply (Shopify). Re-scan to verify.

For agents and developers

Works from CLI, API, and MCP

AI agents discover and invoke tools programmatically. Developers get the same access from the command line.

CLI
colter fix
$colter fix https://my-store.com
Generating fixes for 5 gaps...
✓ webmcp — 6 commerce tools (+15 score)
✓ llms_txt — agent discovery file (+8 score)
✓ robots_txt — unblock AI crawlers (+5 score)
✓ json_ld_product — structured product data (+10 score)
✓ agents_md — agent instructions (+4 score)
5 fixes written to ./colter-fixes/
REST API
REST APIbash
curl -X POST https://agenticcom.ai/api/v1/fix \
  -H "Content-Type: application/json" \
  -d '{"url": "https://my-store.com"}'
 
# Returns: fix_plan with generated_content,
# deploy_instructions, expected_score_lift,
# and llm_prompt for each fix type

Install: npx -y @getcolter/cli · MCP: npx -y @getcolter/cli mcp --admin-tools

Next step

Prove it works with real agents.

Fix generates the code. Test sends AI agents to verify the implementation works end-to-end.

Learn about Test