# H&M — API Agent Score

> Score: 53/100 (Grade: D) | Domain: hm.com | Rubric: 1.0.0 | Checked: July 27, 2026

H&M scored 53/100 (D), classified "not-ai-ready".

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

## Summary

- Overall: 53/100 (D)
- Classification: not-ai-ready

## Category Scores

- API Design: 63/100 (C)
- Developer Experience: 40/100 (F)
- Agent Discovery: 70/100 (B)
- Agent Understanding: 56/100 (D)
- Agent Usability: 45/100 (F)

## Check Results

### API Design

- [warn] Schema coverage & depth — 48/163 (29%) public params are fully typed (no any/**kwargs). Analyzer reports not all methods have a derivable input schema. Investigated: sdk 66%.
- [pass] Example coverage — README is present and includes a runnable quickstart. Investigated: sdk 100%, docs 0%.
- [fail] Security & governance hygiene — No security.txt at /.well-known/security.txt or /security.txt. Investigated: wellknown 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

- [fail] Self-service developer portal — No signup page detected across conventional paths (/signup, /sign-up, /register, /get-started, /console/signup, /dashboard/signup, /try, /try-free, /free, /free-trial, /start, /start-free). Investigated: docs 0%.
- [fail] Quickstart present — No quickstart/getting-started page found at the conventional paths. Investigated: docs 0%.
- [fail] Code samples in docs — No detectable code samples across 1 sampled docs pages. Investigated: docs 0%.
- [fail] Description completeness — 215/215 operations lack a description. Investigated: sdk 0%.
- [skip] Changelog published — No surface produced evidence for this capability in this run.

### Agent Discovery

- [pass] Registry & SDK presence — Indexed on Context7 (vitejs/vite, 1407 snippets). Investigated: docs 100%, sdk 100%, cli 0%, mcp 0%, wellknown 0%.
- [warn] Docs reachable, not hard auth-gated — Server ignores Accept: text/markdown header (0/1 pages return markdown). Investigated: docs 75%.
- [pass] Crawlable / AEO — No robots.txt on the docs host — AI crawlers unrestricted. Investigated: wellknown 100%.
- [fail] llms.txt present, valid & comprehensive — No llms.txt found at any candidate location (https://portal.api.hmgroup.com/llms.txt, https://portal.api.hmgroup.com/docs/llms.txt). Investigated: docs 0%, sdk 0%.

### Agent Understanding

- [warn] Agent-navigable, token-efficient docs — No pages support .md URLs (0/1 tested). Investigated: docs 71%.
- [warn] Docs structured data — OpenGraph/meta tags only across 1 assessed pages — no JSON-LD for answer engines to cite. Investigated: docs 50%.
- [fail] Agent instructions file (AGENTS.md) — No AGENTS.md at the site root or /.well-known/. Investigated: wellknown 0%.
- [fail] Description consistency across surfaces — Mean pairwise description similarity across 2 surfaces (docs, sdk) is 0% (threshold 35% for full credit).
- [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.

### Agent Usability

- [warn] Sandbox separation — No test-mode flag or sandbox environment is exposed. Investigated: sdk 50%.
- [fail] Idempotency documented — No built-in retry machinery was found; transient failures are not retried. Investigated: sdk 0%.
- [fail] Runnable collection with test scripts — No public Postman workspace discovered for the org. Investigated: platform 0%.
- [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.

## Executive Summary

H&M's API program shows promise in agent discovery reachability and schema quality, but two areas demand urgent attention: developer experience and agent understanding are both critically weak, meaning partners cannot onboard themselves, and neither human developers nor AI agents have the context needed to build confidently against the API. Fixing self-service onboarding and description quality first will unblock partner activation; layering in agent-ready artifacts (llms.txt, AGENTS.md, idempotency docs, and runnable collections) will ensure partners' AI agents can reliably execute real workflows without guesswork.