# Argyle — API Agent Score

> Score: 76/100 (Grade: B) | Domain: argyle.com | Rubric: 1.0.0 | Checked: July 24, 2026

Argyle scored 76/100 (B), classified "partially-ready".

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

## Summary

- Overall: 76/100 (B)
- Classification: partially-ready

## Category Scores

- API Design: 91/100 (A+)
- Developer Experience: 82/100 (A)
- Agent Discovery: 100/100 (A+)
- Agent Understanding: 68/100 (C)
- Agent Usability: 53/100 (D)

## Check Results

### API Design

- [pass] Schema coverage & depth — package.json "types" → index.d.ts. Investigated: sdk 100%.
- [pass] Security & governance hygiene — security.txt valid at https://argyle.com/.well-known/security.txt (Contact + unexpired Expires). Investigated: wellknown 100%.
- [warn] Example coverage — README is present but has no runnable quickstart. Investigated: sdk 50%, docs 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 — Self-service signup at https://console.argyle.com/sign-up; no free tier or sandbox language detected. Investigated: docs 100%.
- [pass] Quickstart present — Quickstart at https://docs.argyle.com/quickstart with a runnable first-call sample. Investigated: docs 100%.
- [pass] Changelog published — Newest official SDK activity 3 day(s) ago. Investigated: sdk 100%.
- [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.

### Agent Discovery

- [pass] llms.txt present, valid & comprehensive — llms.txt found at https://docs.argyle.com/llms.txt. Investigated: docs 100%, sdk 0%.
- [pass] Docs reachable, not hard auth-gated — All 50 sampled pages are publicly accessible. Investigated: docs 100%.
- [pass] Registry & SDK presence — Indexed on Context7 (argyleink/open-props, 782 snippets). Investigated: docs 100%, sdk 33%, cli 0%.
- [pass] Crawlable / AEO — Docs paths crawlable by all monitored AI agents. Investigated: wellknown 100%.

### Agent Understanding

- [warn] Agent-navigable, token-efficient docs — 1 of 50 pages exceed 100K chars (max 397K). Investigated: docs 72%.
- [pass] Docs structured data — JSON-LD Article markup on 17/17 assessed pages (100%) with dateModified present. Investigated: docs 100%.
- [fail] Agent instructions file (AGENTS.md) — No AGENTS.md at the site root or /.well-known/. Investigated: wellknown 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 1 surface description(s) with ≥6 tokens available; need at least 2 to compare.

### Agent Usability

- [pass] Sandbox separation — Sandbox environments are exposed (sandbox). Investigated: sdk 100%.
- [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

Argyle's API design and developer experience are strong — partners land on a well-structured, easy-to-evaluate surface. The critical gaps are in agent readiness and operational reliability: there is no machine-readable instruction file for AI agents, no runnable collection with test coverage, and idempotency behavior is undocumented, meaning partners' AI-powered integrations will guess at retry safety and workflow correctness rather than build from authoritative, executable context. Closing these three gaps should be the immediate priority to make Argyle's API program self-serve for both human partners and the agents they increasingly rely on.