# Ezcater — API Agent Score

> Score: 52/100 (Grade: D) | Domain: ezcater.com | Rubric: 1.0.0 | Checked: July 29, 2026

Ezcater scored 52/100 (D), classified "not-ai-ready".

[View full report](https://www.postman.com/ai/ai-ready-apis/company/ezcater)
[All organizations](https://www.postman.com/ai/ai-ready-apis/llms.txt)

## Summary

- Overall: 52/100 (D)
- Classification: not-ai-ready

## Category Scores

- API Design: 40/100 (F)
- Developer Experience: 66/100 (C)
- Agent Discovery: 79/100 (B)
- Agent Understanding: 59/100 (D)
- Agent Usability: 40/100 (F)

## Check Results

### API Design

- [fail] Schema coverage & depth — no .d.ts found. Investigated: sdk 0%.
- [fail] Security & governance hygiene — No security.txt at /.well-known/security.txt or /security.txt. Investigated: wellknown 0%.
- [fail] Example coverage — No detectable code samples across 20 sampled docs pages. Investigated: docs 0%, sdk 0%.
- [skip] Machine-readable, versioned contract — No surface produced evidence for this capability in this run.
- [skip] Auth declared & discoverable — No surface produced evidence for this capability in this run.

### Developer Experience

- [pass] Self-service developer portal — Signup page at https://www.ezcater.com/company/catering-growth-platform/; no free-tier language detected in docs/pricing. Investigated: docs 100%.
- [warn] Quickstart present — Quickstart page reachable (3 variants scanned starting at https://api.ezcater.io/quickstart) but no runnable code sample detected in HTML or .md variant. Investigated: docs 50%.
- [fail] Code samples in docs — No detectable code samples across 20 sampled docs pages. Investigated: docs 0%.
- [skip] Description completeness — No surface produced evidence for this capability in this run.
- [skip] Changelog published — No surface produced evidence for this capability in this run.

### Agent Discovery

- [pass] Registry & SDK presence — Indexed on Context7 (websites/api_ezcater_io, 620 snippets). Investigated: docs 100%, sdk 100%, cli 0%.
- [warn] llms.txt present, valid & comprehensive — No llms.txt directive found in HTML of any of 50 sampled pages. Investigated: docs 69%.
- [warn] Docs reachable, not hard auth-gated — 50 of 50 sampled pages return 200 for non-existent URLs (soft 404). Investigated: docs 50%.
- [pass] Crawlable / AEO — Docs paths crawlable by all monitored AI agents. Investigated: wellknown 100%.

### Agent Understanding

- [warn] Agent-navigable, token-efficient docs — 14 of 50 sampled pages have content starting past 50% (worst 100%). Investigated: docs 85%.
- [fail] Agent instructions file (AGENTS.md) — No AGENTS.md at the site root or /.well-known/. Investigated: wellknown 0%.
- [fail] Docs structured data — Neither JSON-LD nor OpenGraph/meta tags detected across 20 sampled pages — likely a CSR-only docs site. Investigated: docs 0%.
- [skip] Machine-readable errors (RFC 9457) — No surface produced evidence for this capability in this run.
- [skip] Operation purpose clarity — No surface produced evidence for this capability in this run.
- [skip] Description consistency across surfaces — Only 0 surface description(s) with ≥6 tokens available; need at least 2 to compare.

### Agent Usability

- [fail] Runnable collection with test scripts — No public Postman workspace discovered for the org. Investigated: platform 0%.
- [skip] Idempotency documented — No surface produced evidence for this capability in this run.
- [skip] Rate-limit signaling — No surface produced evidence for this capability in this run.
- [skip] Pagination documented & consistent — No surface produced evidence for this capability in this run.
- [skip] Sandbox separation — No surface produced evidence for this capability in this run.

## Executive Summary

Ezcater's API discovery foundation is reasonably solid, but the program has critical gaps in contract quality, agent-readiness, and partner runnability that will block both human and AI-driven integrations. The most urgent priorities are hardening the OpenAPI contract — adding schemas, security definitions, and realistic examples — and making the API executable and verifiable so partners and their agents can build with confidence rather than guessing. Addressing these gaps will meaningfully compress the time from partner interest to live integration and reduce support burden across the program.