# Smarthr — API Agent Score

> Score: 53/100 (Grade: D) | Domain: smarthr.jp | Rubric: 1.0.0 | Checked: July 21, 2026

Smarthr scored 53/100 (D), classified "not-ai-ready".

[View full report](https://www.postman.com/ai/ai-ready-apis/company/smarthr)
[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: 61/100 (C)
- Developer Experience: 56/100 (D)
- Agent Discovery: 65/100 (C)
- Agent Understanding: 45/100 (F)
- Agent Usability: 46/100 (F)

## Check Results

### API Design

- [warn] Machine-readable, versioned contract — info.version="0.0.1" set but no versioning scheme (URL / header / media type) detected. Investigated: spec 75%, docs 50%.
- [warn] Schema coverage & depth — 92% of operations have documented schemas (target 95%+). Investigated: spec 67%, sdk 0%.
- [pass] Security & governance hygiene — No credential-shaped strings detected in spec. Investigated: spec 100%, wellknown 100%.
- [fail] Auth declared & discoverable — No securitySchemes declared. Investigated: spec 0%, docs 0%.
- [fail] Example coverage — 0% example coverage. Investigated: spec 0%, docs 0%, sdk 0%.

### Developer Experience

- [pass] Self-service developer portal — Self-service signup at https://smarthr.jp/signup/; free tier / sandbox documented. Investigated: docs 100%.
- [pass] Changelog published — Newest official SDK activity 0 day(s) ago. Investigated: sdk 100%, spec 0%, 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 — 32% description completeness. Investigated: spec 0%.

### Agent Discovery

- [pass] Registry & SDK presence — Indexed on Context7 (websites/support_smarthr_jp_ja, 1420 snippets). Investigated: docs 100%, sdk 75%, cli 0%.
- [warn] Docs reachable, not hard auth-gated — Server ignores Accept: text/markdown header (0/1 pages return markdown). Investigated: docs 75%.
- [warn] Crawlable / AEO — No sitemap discoverable via robots.txt or /sitemap.xml on the docs host. Investigated: wellknown 50%.
- [fail] llms.txt present, valid & comprehensive — No llms.txt found at any candidate location (https://developer.smarthr.jp/llms.txt, https://developer.smarthr.jp/docs/llms.txt). Investigated: docs 0%.

### Agent Understanding

- [warn] Agent-navigable, token-efficient docs — No pages support .md URLs (0/1 tested). Investigated: docs 79%.
- [fail] Machine-readable errors (RFC 9457) — No 4xx/5xx response codes (or default error response) documented anywhere in the spec. Investigated: spec 0%, docs 0%.
- [fail] Operation purpose clarity — 8% of operations are agent-inferable. Investigated: spec 0%.
- [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 1 assessed pages (1 JS-rendered). Investigated: docs 0%.
- [skip] Description consistency across surfaces — Only 0 surface description(s) with ≥6 tokens available; need at least 2 to compare.

### Agent Usability

- [pass] Pagination documented & consistent — Pagination params detected on 26 list endpoint(s). Investigated: spec 100%, docs 100%.
- [fail] Idempotency documented — 0% of mutating operations document idempotency. Investigated: spec 0%, docs 0%.
- [fail] Rate-limit signaling — No rate-limit response headers documented. Investigated: spec 0%, docs 0%.
- [fail] Sandbox separation — No sandbox/test server declared across 1 server entries; no test-key prefixes documented. Investigated: spec 0%, docs 0%.
- [fail] Runnable collection with test scripts — No public Postman workspace discovered for the org. Investigated: platform 0%.

## Executive Summary

Smarthr's API program shows strength in basic contract structure, but agent understanding and agent usability are critically underdeveloped — partners and their AI agents cannot reliably parse errors, understand operation intent, or run safe end-to-end workflows. The most urgent priorities are making the API surface interpretable and executable for agents (structured error semantics, operation clarity, and runnable examples), then closing the discoverability and onboarding gaps that slow every new partner's first integration.