isagentready
v0.3.0
Published
Scan any website for AI agent readiness from your terminal: scores, grades, and per-checkpoint fix steps and verify commands
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@isagentready/cli
Scan any website for AI agent readiness from your terminal. Get scores, letter grades, and fix steps for each checkpoint. Run isagentready checkpoints for the live list of checkpoints.
Built for both humans and AI agents. When you pipe the output, the CLI changes to JSON output.
$ isagentready scan example.com
A+ example.com 98/100
Scanned in 1.7s
Categories
███████████████ 100% AI Content Discovery (30% weight)
█████████████░░ 89% AI Search Signals (20% weight)
███████████████ 100% Content & Semantics (20% weight)
███████████████ 100% Agent Protocols (15% weight)
███████████████ 100% Security & Trust (15% weight)Install
npm install -g @isagentready/cliOr use directly with npx:
npx @isagentready/cli scan example.comCommands
isagentready scan <url>
Scan a website and wait for results.
isagentready scan example.com
isagentready scan https://example.com --verbose # Show all checkpoints, fix steps and verify commands
isagentready scan example.com --json # Machine-readable JSON output
isagentready scan example.com --dry-run # Validate URL without scanning
isagentready scan example.com --no-poll # Start scan without waiting
isagentready scan example.com --fields domain,overall_score,letter_gradeisagentready results <domain>
Get the latest scan results for a domain.
isagentready results example.com
isagentready results example.com --verbose
isagentready results example.com --json --fields domain,overall_score,letter_grade
isagentready results example.com --failing # Only fail and partial checkpoints that apply
isagentready results example.com --checkpoint ia.a2a-agent-card # One checkpoint (stable or legacy id)For failing checkpoints, the text output shows the stable id, the stage and the strength. --verbose adds the fix steps and the verify command.
isagentready checkpoints
List the checkpoint definitions of the current methodology: stable id, legacy id, stage (Find, Read, Act), strength (MUST, SHOULD, MAY) and name.
isagentready checkpoints
isagentready checkpoints --stage act --strength MUST
isagentready checkpoints --category agent_protocols --json
isagentready checkpoints --ar AR-FIND-01isagentready explain <id>
Show one checkpoint: why it matters, the fix steps, the verify command, the agentready.org practice mapping and the fail rate in the latest benchmark. The id can be a stable id (ia.robots-txt) or a legacy id (1.1, or te.1 for a training exposure check).
isagentready explain ia.a2a-agent-card
isagentready explain 4.3 --jsonisagentready methodology
Show the versioned methodology. The scoring weights are a separate document.
isagentready methodology # Current version, stages, latest change
isagentready methodology --version 2026-09-02
isagentready methodology --changelog
isagentready methodology --scoring # Category weights and grade bandsisagentready verify <id> <domain>
Get the status of one checkpoint and print its read-only verify command. The CLI prints the command for you to run. It never runs the command. The exit code is 5 when the checkpoint applies to the site and its status is fail or partial. In all other cases the exit code is 0. The outcome field in the JSON output tells you why: pass, fail, not_applicable, skipped or informational.
isagentready verify ia.a2a-agent-card example.com
isagentready verify ia.a2a-agent-card example.com --rescan # Start a new scan firstisagentready rankings
Browse the AI agent readiness leaderboard.
isagentready rankings
isagentready rankings --page 2 --per-page 10
isagentready rankings --grade high # A/A+ only
isagentready rankings --search "example"
isagentready rankings --sort newest --json
isagentready rankings --page-all --fields domain,overall_score # Stream all as NDJSONisagentready schema [command]
Dump CLI schema as JSON for runtime introspection by AI agents.
isagentready schema # Full CLI schema
isagentready schema scan # Schema for scan command onlyThe schema also describes the output JSON shape of each command.
Agent-friendly features
This CLI follows the patterns from Rewrite Your CLI for AI Agents:
Auto-detect non-TTY
When you pipe or redirect stdout, the CLI writes JSON. You do not need the --json flag:
# Piped: JSON output
isagentready results example.com | jq '.overall_score'
# Interactive terminal: colored text output
isagentready results example.comOutput format control
--json # Explicit JSON flag
--output json|text # Explicit format override
OUTPUT_FORMAT=json # Environment variableField masks
Limit response size to stay within context windows:
isagentready results example.com --fields domain,overall_score,letter_grade
isagentready results example.com --failing --fields domain,categories.checkpoints.stable_id,categories.checkpoints.failureA dot path selects a nested field. A path step into an array applies the rest of the path to each element.
NDJSON streaming
Stream all ranked websites as newline-delimited JSON:
isagentready rankings --page-all --fields domain,overall_score | wc -lDry run
Validate inputs without hitting the API:
isagentready scan example.com --dry-runRuntime introspection
AI agents can discover capabilities at runtime:
isagentready schema # All commands as JSON
isagentready schema scan # Single command schemaInput validation
All inputs are validated against adversarial patterns (path traversal, control characters, URL-encoded sequences, embedded query params).
Meaningful exit codes
| Code | Meaning |
|------|---------|
| 0 | Success |
| 1 | General error (network, API) |
| 2 | Validation error (invalid input) |
| 3 | Scan failed |
| 4 | Not found |
| 5 | verify: the checkpoint applies to the site and its status is fail or partial |
Agent guidance
The package includes CONTEXT.md. This file tells AI agents the CLI conventions, invariants and good practices.
What it checks
The scanner uses a versioned set of checkpoints. It puts each checkpoint in one stage of the agentready.org spec: Find, Read or Act. Run isagentready checkpoints for the live list, and isagentready methodology --scoring for the current category weights.
| Category | Examples | |---|---| | AI Content Discovery | robots.txt, AI crawlers, sitemap, llms.txt, meta robots | | AI Search Signals | JSON-LD, Schema.org, entity linking, FAQPage, author attribution | | Content & Semantics | SSR, heading hierarchy, semantic HTML, ARIA, accessibility | | Agent Protocols | WebMCP, A2A, MCP discovery, OpenAPI, agents.json | | Security & Trust | HTTPS, HSTS, CSP, security headers, CORS |
Requirements
- Node.js 18+ (uses native
fetch)
License
MIT
