Colter Fix

TL;DR: Run colter fix https://your-store.com --dry-run to see the plan, then add --apply when you want generated files written out. The output is structured and ranked by estimated score impact.

colter.fix returns machine-readable fix plans designed for agent workflows, review tools, and CI systems.

What Fix Generates

Output	Purpose
JSON-LD	Product and store structured data
Open Graph tags	Agent-friendly content previews
llms.txt	Agent discovery and guidance
robots.txt patch	Unblock important crawlers
UCP manifest	Google ecosystem protocol support
MCP config	Tool discovery for MCP clients
A2A card	Multi-agent discovery metadata

CLI

colter fix <url> [flags]

Common Flags

Flag	Purpose
--apply	Write generated files
--dry-run	Generate content without writing
--json	Machine-readable output
`--format json	liquid`
--output-dir DIR	Output directory
`--platform file	shopify
--test-json FILE	Reuse a saved test result
--evidence	Generate an Evidence Pack after apply
--api-url URL	Override API base URL
-v, --verbose	Verbose logging

Examples

Review the plan:

colter fix https://store.example.com --dry-run

Write files locally:

colter fix https://store.example.com --apply --output-dir ./colter-fixes

Apply to Shopify:

colter fix https://store.example.com --apply --platform shopify

Emit JSON:

colter fix https://store.example.com --json

Adapters

Adapter	When to use it
file	Review files before deployment
shopify	Apply through Shopify integration
rest	Push generated output to a custom backend

Output Shape

The JSON plan includes:

• score_before
• score_after_est
• platform
• ops[] sorted by score_impact

Each operation includes a target, dimension, risk level, and optional generated content.

Recommended Flow

1. Run Check first.
2. Review the fix plan.
3. Apply safe fixes.
4. Re-run Check or Verify.

Next Steps

• Check
• Lens
• Scoring Model
• Evidence Packs
• Pricing
• API Reference